Books
2016
1. René Vidal, Yi Ma, and Shankar Sastry.
   Generalized Principal Component Analysis
   Springer Verlag, 2016.
   Download: [HTML] 


2007
2. R. Vidal, A. Heyden, and Y. Ma, editors.
   Dynamical Vision
   Springer Verlag, January 2007.
   Download: [HTML] 


Journals
2022
3. Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele, René Vidal, and Donald Geman.
   Interpretable by Design: Learning Predictors by Composing Interpretable Queries.
   IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1–14, 2022.
   Download: [pdf] 


4. Carolina Pacheco, Gregory N. McKay, Anisha Oommen, Nicholas J. Durr, René Vidal, and Benjamin D. Haeffele.
   Adaptive sparse reconstruction for lensless digital holography via PSF estimation and phase retrieval.
   Optics Express, pp. 33433–33448, 2022.
   Download: [HTML] 


2021
5. Guilherme Franca, Daniel P. Robinson, and René Vidal.
   Gradient flows and proximal splitting methods: A unified view on accelerated and stochastic optimization.
   Phys. Rev. E, 103:053304, 2021.
   Download: [pdf] [ps.gz] [ps] [HTML] [poster] [slides] [code] 


6. G. Franca, M. Jordan, and R. Vidal.
   On Dissipative Symplectic Integration with Applications to Gradient-Based Optimization.
   Journal of Statistical Mechanics: Theory and Experiment, 2021(4):043402, 2021.
   Download: [pdf] [ps.gz] [ps] [HTML] [poster] [slides] [code] 


7. Mustafa Kaba, Mengnan Zhao, Rene Vidal, Daniel P. Robinson, and Enrique Mallada.
   What Is the Largest Sparsity Pattern That Can Be Recovered by 1-Norm Minimization?.
   IEEE Transactions on Information Theory, 67(5):3060–3074, 2021.
   Download: [HTML] 


8. Rene Vidal, Benjamin D Haeffele, and Zhihui Zhu.
   Optimization Landscape of Neural Networks.
   In Theory of Deep Learning, Cambridge University Press, 2021.
   Download: [pdf] 


2020
9. J. Bruna, E. Haber, G. Kutyniok, R. Vidal, and T. Pock.
   Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science.
   Journal of Mathematical Imaging and Vision, 62:277–278, 2020.
   Download: [pdf] 


10. G. Franca, J. Sulam, D. P. Robinson, and R. Vidal.
    Conformal Symplectic and Relativistic Optimization.
    Journal of Statistical Mechanics: Theory and Experiment, 2020(12):124008, 2020.
    Download: [pdf] [ps.gz] [ps] [HTML] [poster] [slides] [code] 


11. Benjamin D Haeffele, Christian Pick, Ziduo Lin, Evelien Mathieu, Stuart C Ray, and René Vidal.
    Generative optical modeling of whole blood for detecting platelets in lens-free images.
    Biomedical optics express, 11(4):1808–1818, Optical Society of America, 2020.
    Download: (unavailable)


12. E. Kokkoni, E. Mavroudi, A. Zehfroosh, J. C. Galloway, R. Vidal, J. Heinz, and H. Tanner.
    GEARing smart environments for pediatric motor rehabilitation.
    Journal of NeuroEngineering and Rehabilitation, 17, 2020.
    Download: [pdf] [HTML] 


13. Xiao Li, Zhihui Zhu, Anthony Man-Cho So, and Rene Vidal.
    Nonconvex robust low-rank matrix recovery.
    SIAM Journal on Optimization, 30(1):660–686, 2020.
    Download: [pdf] [HTML] 


14. H. Lobel, R. Vidal, and A. Soto.
    CompactNets: Compact Hierarchical Compositional Networks for Visual Recognition.
    Computer Vision and Image Understanding, 191, 2020.
    Download: [pdf] 


15. B. Tuncgenc, C. Pacheco, R. Rochowiak, R. Nicholas, S. Rengarajan, E. Zou, B. Messenger, R. Vidal, and S. Mostofsky.
    Computerised Assessment of Motor Imitation (CAMI) as a scalable method for distinguishing children with autism.
    Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, Elsevier, 2020.
    Download: [HTML] 


16. Chong You, Chi Li, Daniel Robinson, and Rene Vidal.
    Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020.
    Download: [pdf] 


2019
17. G. Franca, J. Sulam, D. P. Robinson, and R. Vidal.
    Conformal Symplectic and Relativistic Optimization.
    arXiv:1903.04100 [math.OC], 2019.
    Download: (unavailable)


18. Benjamin D Haeffele and René Vidal.
    Structured low-rank matrix factorization: Global optimality, algorithms, and applications.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(6):1468–1482, IEEE, 2019.
    Download: [pdf] 


19. Ambar Pal, Connor Lane, René Vidal, and Benjamin D Haeffele.
    On the Regularization Properties of Structured Dropout.
    arXiv preprint arXiv:1910.14186, 2019.
    Download: [pdf] [HTML] 


20. Evan Schwab, Benjamin D Haeffele, René Vidal, and Nicolas Charon.
    Global optimality in separable dictionary learning with applications to the analysis of diffusion MRI.
    SIAM Journal on Imaging Sciences, 12(4):1967–2008, SIAM, 2019.
    Download: [pdf] [HTML] 


2018
21. G. Franca, D. P. Robinson, and R. Vidal.
    A Dynamical Systems Perspective on Nonsmooth Constrained Optimization.
    arXiv:1808.04048 [math.OC], 2018.
    Download: (unavailable)


22. Hao Jiang, Daniel P Robinson, René Vidal, and Chong You.
    A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis.
    Computational Optimization and Applications, 70(2):395–418, Springer, 2018.
    Download: [pdf] 


23. Chun-Guang Li, Chong You, and René Vidal.
    On Geometric Analysis of Affine Sparse Subspace Clustering.
    IEEE Journal on Selected Topics in Signal Processing, 12(6):1520–1533, 2018.
    Download: [pdf] [HTML] 


24. E. Schwab, R. Vidal, and N. Charon.
    Joint Spatial-Angular Sparse Coding for Diffusion MRI with Separable Dictionaries.
    Medical Image Analysis, 48:25–42, 2018.
    Download: [pdf] [HTML] 


25. Manolis C. Tsakiris and René Vidal.
    Dual Principal Component Pursuit.
    Journal of Machine Learning Research, 18(19):1–50, 2018.
    Download: [pdf] 


26. M. C. Tsakiris and R. Vidal.
    Theoretical Analysis of Sparse Subspace Clustering with Missing Entries.
    arXiv:1801.00393, 2018.
    Download: [pdf] 


27. Z. Zhu, Y. Wang, D. Robinson, D. Naiman, R. Vidal, and M. Tsakiris.
    Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms.
    arXiv preprint arXiv:1812.09924, 2018.
    Download: [pdf] [HTML] 


2017
28. B. Afsari and R. Vidal.
    Bundle Reduction and the Alignment Distance on Spaces of State-Space LTI Systems.
    IEEE Transactions on Automatic Control, 62(8):3804–3819, 2017.
    Download: [pdf] [HTML] 


29. N. Ahmidi, L. Tao, S. Sefati, Y. Gao, C. Lea, B. Béjar, L. Zappella, S. Khudanpur, R. Vidal, and G. D. Hager.
    A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery.
    IEEE Transactions on Biomedical Engineering, 2017.
    Download: [HTML] 


30. Benjamin D. Haeffele and René Vidal.
    Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications.
    CoRR, abs/1708.07850, 2017.
    Download: (unavailable)


31. E. Jahangiri, E. Yoruk, R. Vidal, L. Younes, and D. Geman.
    Information Pursuit: A Bayesian Framework for Sequential Scene Parsing.
    Arxiv, 2017.
    Download: [pdf] 


32. Chun-Guang Li, Chong You, and René Vidal.
    Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework.
    IEEE Transactions on Image Processing, 26(6):2988–3001, 2017.
    Download: [pdf] [ps.gz] [ps] [HTML] [poster] [slides] [code] 


33. M. Petreczky and R. Vidal.
    Realization Theory for a Class of Stochastic Bilinear Systems.
    IEEE Transactions on Automatic Control, 63(1):69–84, 2017.
    Download: [HTML] 


34. E. Schwab, R. Vidal, and N. Charon.
    Joint Spatial-Angular Sparse Coding for Diffusion MRI with Separable Dictionaries.
    ArXiv, 2017.
    Download: [HTML] 


35. Manolis C. Tsakiris and René Vidal.
    Algebraic clustering of affine subspaces.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(2):482–489, 2017.
    Download: [pdf] 


36. M. C. Tsakiris and R. Vidal.
    Dual Principal Component Pursuit.
    arXiv:1510.04390v2 [cs.CV], 2017.
    Download: [pdf] 


37. M. C. Tsakiris and R. Vidal.
    Hyperplane clustering via dual principal component pursuit.
    arXiv:1706.01604 [cs.CV], 2017.
    Download: [pdf] 


38. M. C. Tsakiris and R. Vidal.
    Filtrated algebraic subspace clustering.
    SIAM Journal on Imaging Sciences, 10(1):372–415, 2017.
    Download: [pdf] 


39. R. Vidal, R. Giryes, J. Bruna, and S. Soatto.
    Mathematics of Deep Learning.
    arXiv:1712.0474, 2017.
    Download: [pdf] 


40. C. You, D. Robinson, and R. Vidal.
    Provable Self-Representation Based Outlier Detection in a Union of Subspaces.
    Arxiv, 2017.
    Download: [HTML] 


2016
41. B. Afsari and R. Vidal.
    Model Order Reduction in the Alignment Distance and Metrization of the Kalman Decomposition.
    IEEE Transactions on Automatic Control, (Under Review) 2016.
    Download: [pdf] 


42. C. Lea, M.D. Flynn, R. Vidal, A. Reiter, and G. D. Hager.
    Temporal Convolutional Networks for Action Segmentation and Detection.
    arXiv, 2016.
    Download: [pdf] 


43. C.-G. Li and R. Vidal.
    A Structured Sparse plus Structured Low-Rank Framework for Subspace Clustering and Completion.
    IEEE Transactions on Signal Processing, 64(24):6557–6570, 2016.
    Download: [pdf] [ps.gz] [ps] [HTML] [poster] [slides] [code] 


44. S Swaroop Vedula, Anand O Malpani, Lingling Tao, George Chen, Yixin Gao, Piyush Poddar, Narges Ahmidi, Christopher Paxton, Rene Vidal, Sanjeev Khudanpur, Gregory D Hager, and Chi Chiung Grace Chen.
    Analysis of the Structure of Surgical Activity for a Suturing and Knot-Tying Task.
    PloS one, 11(3), 2016.
    Download: [HTML] 


45. C. You, C.-G. Li, D. Robinson, and R. Vidal.
    Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering.
    Arxiv, 2016.
    Download: [HTML] 


2015
46. Benjamin D Haeffele and René Vidal.
    Global Optimality in Tensor Factorization, Deep Learning, and Beyond.
    arXiv preprint arXiv:1506.07540, abs/1506.07540, 2015.
    Download: [pdf] [HTML] 


47. H. Lobel, R. Vidal, and A. Soto.
    Learning Shared, Discriminative, and Compact Representations for Visual Recognition.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(11):2218–2231, 2015.
    Download: [HTML] 


48. V. M. Patel, H. V. Nguyen, and R. Vidal.
    Latent Space Sparse and Low-rank Subspace Clustering.
    IEEE Journal of Selected Topics in Signal Processing, 9(4):691–701, 2015.
    Download: [HTML] 


49. C. You and R. Vidal.
    Subspace-Sparse Representation.
    Arxiv, abs/1507.01307, 2015.
    Download: [HTML] 


50. C. You, D. Robinson, and R. Vidal.
    Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit.
    Arxiv, abs/1507.01238, 2015.
    Download: [HTML] 


2014
51. B. Afsari and R. Vidal.
    Distances on Spaces of High-Dimensional Linear Stochastic Processes: A Survey.
    In Geometric Theory of Information, Signals and Communication Technology, pp. 219–242, Spinger-Verlag, 2014.
    Download: [pdf] [HTML] 


52. H. E. Cetingül, M. Wright, P. Thompson, and R. Vidal.
    Segmentation of High Angular Resolution Diffusion MRI using Sparse Riemannian Manifold Clustering.
    IEEE Transactions on Medical Imaging, 33(2):301–317, 2014.
    Download: [HTML] 


53. G. Gorospe, R. Zhu, M. Millrod, E. Zambidis, L. Tung, and R. Vidal.
    Automated Grouping of Action Potentials of Human Embryonic Stem Cell-Derived Cardiomyocytes.
    IEEE Transactions on Biomedical Engineering, 61(9):2389–2395, 2014.
    Download: [pdf] [HTML] 


54. F. Ofli, R. Chaudhry, G. Kurillo, R. Vidal, and R. Bajcsy.
    Sequence of the Most Informative Joints (SMIJ): A New Representation for Human Skeletal Action Recognition.
    Journal of Visual Communication and Image Representation, 25(1):24–38, 2014.
    Download: [pdf] [HTML] 


55. R. Tron and R. Vidal.
    Distributed 3-D Localization of Camera Sensor Networks From 2-D Image Measurements.
    IEEE Transactions on Automatic Control, 59(12):3325–3340, 2014.
    Download: [HTML] 


56. René Vidal and Paolo Favaro.
    Low Rank Subspace Clustering (LRSC).
    Pattern Recognition Letters, 43:47–61, 2014.
    Download: [pdf] [HTML] 


2013
57. B. Afsari, R. Tron, and R. Vidal.
    On the Convergence of Gradient Descent for Locating the Riemmanian Center of Mass.
    SIAM Journal on Control and Optimization, 51(3):2230–2260, 2013.
    Download: [pdf] [HTML] 


58. R. Chaudhry, G. Hager, and R. Vidal.
    Dynamic Template Tracking and Recognition.
    International Journal of Computer Vision, 105(1):19–48, 2013.
    Download: [pdf] [HTML] 


59. Ehsan Elhamifar and René Vidal.
    Sparse Subspace Clustering: Algorithm, Theory, and Applications.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(11):2765–2781, 2013.
    Download: [pdf] [HTML] 


60. A. Ravichandran, R. Chaudhry, and R. Vidal.
    Categorizing Dynamic Textures using a Bag of Dynamical Systems.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(2):342–353, 2013.
    Download: [pdf] [HTML] 


61. R. Tron, B. Afsari, and R. Vidal.
    Riemannian Consensus for Manifolds with Bounded Curvature.
    IEEE Transactions on Automatic Control, 58(4):921–934, 2013.
    Download: [pdf] [HTML] 


62. L. Zappella, B. Béjar, G. Hager, and R. Vidal.
    Surgical Gesture Classification from Video and Kinematic data.
    Medical Image Analysis, 17(7):732 – 745, 2013.
    Download: [pdf] [HTML] 


2012
63. E. Elhamifar and R. Vidal.
    Block-Sparse Recovery via Convex Optimization.
    IEEE Transactions on Signal Processing, 60(8):4094–4107, 2012.
    Download: [HTML] 


2011
64. H. E. Cetingül, G. Plank, N. Trayanova, and R. Vidal.
    Estimation of Local Orientations in Fibrous Structures with Applications to the Purkinje System.
    IEEE Transactions on Biomedical Engineering, 58(6):1762–1772, February 2011.
    Download: [HTML] 


65. A. Goh, C. Lenglet, P. Thompson, and R. Vidal.
    A Nonparametric Riemannian Framework for Processing High Angular Resolution Diffusion Images and its Applications to ODF-based Morphometry.
    Neuroimage, 47(3):608–613, February 2011.
    Download: [HTML] 


66. F. Lauer, G. Bloch, and R. Vidal.
    A Continuous Optimization Framework for Hybrid System Identification.
    Automatica, 47:608–613, March 2011.
    Download: [HTML] 


67. A. Ravichandran and R. Vidal.
    Video Registration Using Dynamic Textures.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(1):158–171, January 2011.
    Download: [pdf] [HTML] 


68. D. Singaraju, L. Grady, A. Sinop, and R. Vidal.
    Continuous Valued MRFs for Image Segmentation.
    In Advances in Markov Random Fields for Vision and Image Processing, MIT Press, September 2011.
    Download: [pdf] [HTML] 


69. D. Singaraju and R. Vidal.
    Estimation of Alpha Mattes for Multiple Layers.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(7):1295–1309, July 2011.
    Download: [pdf] [HTML] 


70. R. Tron, A. Terzis, and R. Vidal.
    Distributed Image-Based 3-D Localization in Camera Sensor Networks.
    In Distributed Video Sensor Networks, Springer, 2011.
    Download: [HTML] 


71. R. Tron and R. Vidal.
    Distributed Computer Vision Algorithms.
    IEEE Signal Processing Magazine, 28(2):32–45, May 2011.
    Download: [HTML] 


72. R. Vidal.
    Subspace Clustering.
    IEEE Signal Processing Magazine, 28(3):52–68, March 2011.
    Download: [pdf] [HTML] 


2010
73. Shankar Rao, Roberto Tron, René Vidal, and Yi Ma.
    Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(10):1832–1845, 2010.
    Download: [pdf] [HTML] 


2009
74. J. Daafouz, M.D. Di Benedetto, V.D. Blondel, G. Ferrari-Trecate, L. Hetel, M. Johansson, A.l. Juloski, S. Paoletti, G. Pola, E. De Santis, and R. Vidal.
    Switched and Piecewise Affine Systems.
    In Handbook of Hybrid Systems Control, Theory, Tools, Application, pp. 87–137, Cambridge University Press, 2009.
    Download: [HTML] 


2008
75. R. Vidal.
    Recursive Identification of Switched ARX Systems.
    Automatica, 44(9):2274–2287, September 2008.
    Download: [HTML] 


76. René Vidal, Roberto Tron, and Richard Hartley.
    Multiframe Motion Segmentation with Missing Data Using PowerFactorization, and GPCA.
    International Journal of Computer Vision, 79(1):85–105, 2008.
    Download: [HTML] 


77. R. Vidal and R. Hartley.
    Three-View Multibody Structure from Motion.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2):214–227, February 2008.
    Download: [HTML] 


2007
78. S. Paoletti, A. Juloski, G. Ferrari-Trecate, and R. Vidal.
    Identification of Hybrid Systems: A Tutorial.
    European Journal of Control, 73(1):242–260, 2007.
    Download: [pdf] 


79. S.V.N. Vishwanathan, A. Smola, and R. Vidal.
    Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes.
    International Journal of Computer Vision, 73(1):95–119, 2007.
    Download: [HTML] 


2006
80. R. Vidal, Y. Ma, S. Soatto, and S. Sastry.
    Two-View Multibody Structure from Motion.
    International Journal of Computer Vision, 68(1):7–25, 2006.
    Download: [pdf] 


81. R. Vidal.
    Segmentation of Dynamic Scenes Taken by a Central Panoramic Camera.
    In Imaging Beyond the Pinhole Camera, LNCS, Springer Verlag, 2006.
    Download: [HTML] 


82. R. Vidal and Y. Ma.
    A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation.
    Journal of Mathematical Imaging and Vision, 25(3):403–421, 2006.
    Download: [pdf] 


2005
83. A. Ghoreyshi, R. Vidal, and D. Mery.
    Segmentation of Circular Casting Defects Using a Robust Algorithm.
    Insight, Journal of the British Institute of Non-Destructive Testing, 47(10):615–617, 2005.
    Download: [HTML] 


84. René Vidal, Yi Ma, and Shankar Sastry.
    Generalized Principal Component Analysis (GPCA).
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(12):1–15, 2005.
    Download: [pdf] 


2004
85. Y. Ma, Kun Huang, R. Vidal, J. Kosecká, and S. Sastry.
    Rank Conditions on the Multiple View Matrix.
    International Journal of Computer Vision, 59(2):115–137, 2004.
    Download: [pdf] 


86. R. Vidal, O. Shakernia, and S. Sastry.
    Following the Flock: Distributed Formation Control with Omnidirectional Vision-Based Motion Segmentation and Visual Servoing.
    IEEE Robotics and Automation Magazine, 11(4):14–20, 2004.
    Download: [pdf] 


2002
87. R. Vidal, O. Shakernia, J. Kim, D. Shim, and S. Sastry.
    Probabilistic Pursuit-Evasion Games: Theory, Implementation and Experimental Evaluation.
    IEEE Transactions on Robotics and Automation, 18(5):662–669, 2002.
    Download: [pdf] 


2001
88. J. Concha, A. Cipriano, and R. Vidal.
    Design of fuzzy controllers based on stability analysis.
    Fuzzy Sets and Systems, Special Issue on Formal Methods for Fuzzy Modeling and Control, 121(1):25–38, 2001.
    Download: [HTML] 


89. Y. Ma, R. Vidal, S. Hsu, and S. Sastry.
    Optimal Motion Estimation from Multiple Images by Normalized Epipolar Constraint.
    Journal of Communications in Information and Systems, 1:51–73, 2001.
    Download: [pdf] 


2000
90. J. Concha, A. Cipriano, and R. Vidal.
    Design of Stable Fuzzy Controllers for Nonlinear Processes.
    In Stability Issues in Fuzzy Control, Springer Verlag, 2000.
    Download: (unavailable)


1998
91. A. Cipriano, M. Guarini, R. Vidal, A. Soto, C. Sepúlveda, D. Mery, and H. Brise no.
    A Real Time Visual Sensor for Supervision of Flotation Cells.
    Minerals Engineering, 11(837):489–499, 1998.
    Download: [HTML] 


Refereed Conferences
2023
92. Aditya Chattopadhyay, Xi Zhang, David Paul Wipf, Himanshu Arora, and René Vidal.
    Learning Graph Variational Autoencoders With Constraints and Structured Priors for Conditional Indoor 3D Scene Generation.
    In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 785–794, January 2023.
    Download: [pdf] 


2022
93. Tianjiao Ding, Derek Lim, René Vidal, and Benjamin D. Haeffele.
    Understanding Doubly Stochastic Clustering.
    In International Conference on Machine Learning, pp. 5153–5165, 2022.
    Download: [pdf] 


94. Liangzu Peng, Manolis C. Tsakiris, and René Vidal.
    ARCS: Accurate Rotation and Correspondences Search.
    In IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022.
    Download: [pdf] 


95. Liangzu Peng, Mahyar Fazlyab, and René Vidal.
    Semidefinite relaxations of truncated least-squares in robust rotation search: Tight or not.
    In European Conference on Computer Vision, 2022.
    Download: [pdf] 


96. Liangzu Peng, Christian Kümmerle, and Rene Vidal.
    Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression.
    In Advances in Neural Information Processing Systems, 2022.
    Download: [pdf] 


97. Yutao Tang, Benjamin Béjar, Joey K.-Y Essoe, Joseph F. McGuire, and René Vidal.
    Facial Tic Detection in Untrimmed Videos of Tourette Syndrome Patients.
    In IEEE International Conference on Pattern Recognition, 2022.
    Download: [HTML] 


98. Darshan Thaker, Paris Giampouras, and René Vidal.
    Reverse Engineering $ell_p$ attacks: A block-sparse optimization approach with recovery guarantees.
    In International Conference on Machine Learning, 2022.
    Download: [pdf] 


2021
99. Tianyu Ding, Zhihui Zhu, Daniel Robinson, and René Vidal.
    Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach.
    In International Conference on Machine Learning, 2021.
    Download: [pdf] [HTML] 


100. Benjamin D Haeffele, Chong You, and René Vidal.
     A critique of self-expressive deep subspace clustering.
     International Conference on Learning Representations, 2021.
     Download: [pdf] 


101. Mustafa Kaba, Chong You, Daniel P. Robinson, Enrique Mallada, and René Vidal.
     A Nullspace Property for Subspace-Preserving Recovery.
     In International Conference on Machine Learning, 2021.
     Download: [pdf] [HTML] 


102. Hancheng Min, Salma Tarmoun, René Vidal, and Enrique Mallada.
     On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks.
     In International Conference on Machine Learning, 2021.
     Download: [pdf] [HTML] 


103. Salma Tarmoun, Guilherme Franca, Benjamin Haeffele, and René Vidal.
     Understanding the Dynamics of Gradient Flow in Overparameterized Linear Models.
     In International Conference on Machine Learning, 2021.
     Download: [pdf] [HTML] 


104. Shangzhi Zhang, Chong You, René Vidal, and Chun-Guang Li.
     Learning a Self-Expressive Network for Subspace Clustering.
     In IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021.
     Download: [pdf] 


2020
105. Tianjiao Ding, Yunchen Yang, Zhihui Zhu, Daniel P Robinson, René Vidal, Laurent Kneip, and Manolis C Tsakiris.
     Robust Homography Estimation via Dual Principal Component Pursuit.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 6080–6089, 2020.
     Download: [pdf] 


106. Paris Giampouras, René Vidal, Athanasios Rontogiannis, and Benjamin D. Haeffele.
     A Novel Variational form of the Schatten-p Quasi-norm.
     In Neural Information Processing Systems, 2020.
     Download: [pdf] 


107. E. Mavroudi, B.B. Haro, and R. Vidal..
     Representation Learning on Visual-Symbolic Graphs for Video Understanding.
     In European Conference on Computer Vision, 2020.
     Download: [pdf] [HTML] 


108. C. Pacheco, E. Mavroudi, E. Kokkoni, H. Tanner, and R. Vidal.
     A Detection-based Approach to Multiview Action Classification in Infants.
     In IEEE International Conference on Pattern Recognition, 2020.
     Download: [pdf] 


109. Ambar Pal and Rene Vidal.
     A Game Theoretic View of Additive Adversarial Attacks and Defenses.
     In Neural Information Processing Systems, NIPS, 2020.
     Download: [pdf] 


110. Ambar Pal, Connor Lane, René Vidal, and Benjamin D Haeffele.
     On the regularization properties of structured dropout.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 7671–7679, 2020.
     Download: (unavailable)


2019
111. Tianyu Ding, Zhihui Zhu, Tianjiao Ding, Yunchen Yang, Daniel Robinson, René Vidal, and Manolis Tsakiris.
     Noisy Dual Principal Component Pursuit.
     In International Conference on Machine Learning, 2019.
     Download: [pdf] [HTML] 


112. Benjamin D Haeffele, Christian Pick, Ziduo Lin, Evelien Mathieu, Stuart C Ray, and René Vidal.
     An optical model of whole blood for detecting platelets in lens-free images.
     In MICCAI International Workshop on Simulation and Synthesis in Medical Imaging, pp. 140–150, 2019.
     Download: (unavailable)


113. Connor Lane, Benjamin D. Haeffele, and René Vidal.
     Adaptive online $k$-subspaces with cooperative re-initialization.
     In IEEE International Conference on Computer Vision Workshops, 2019.
     Download: (unavailable)


114. Connor Lane, Ron Boger, Chong You, Manolis Tsakiris, Benjamin Haeffele, and Rene Vidal.
     Classifying and Comparing Approaches to Subspace Clustering with Missing Data.
     In IEEE International Conference on Computer Vision Workshops, 2019.
     Download: (unavailable)


115. E. Mavroudi, B.B. Haro, and R.Vidal.
     Neural Message Passing on Hybrid Spatio-Temporal Visual and Symbolic Graphs for Video Understanding.
     Arxiv, abs/1905.07385, 2019.
     Download: [HTML] 


116. Carolina Pacheco and René Vidal.
     An Unsupervised Domain Adaptation Approach to Classification of Stem Cell-Derived Cardiomyocytes.
     In Medical Image Computing and Computer Assisted Intervention, 2019.
     Download: [pdf] [poster] 


117. Florence Yellin, Benjamín Béjar, Benjamin D Haeffele, Evelien Mathieu, Christian Pick, Stuart C Ray, and René Vidal.
     Joint Holographic Detection and Reconstruction.
     In MICCAI International Workshop on Machine Learning in Medical Imaging, pp. 664–672, 2019.
     Download: (unavailable)


118. Chong You, Chun-Guang Li, Daniel P. Robinson, and René Vidal.
     Is an Affine Constraint Needed for Affine Subspace Clustering?.
     In IEEE International Conference on Computer Vision, 2019.
     Download: [pdf] 


119. Z. Zhu, T. Ding, M. C. Tsakiris, D. P. Robinson, and R. Vidal.
     A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning.
     In Neural Information Processing Systems, 2019.
     Download: (unavailable)


2018
120. Jacopo Cavazza, Benjamin D Haeffele, Connor Lane, Pietro Morerio, Vittorio Murino, and Rene Vidal.
     Dropout as a Low-Rank Regularizer for Matrix Factorization.
     In International Conference on Artificial Intelligence and Statistics, pp. 435–444, 84, 2018.
     Download: [pdf] [HTML] 


121. G. Franca, D. P. Robinson, and R. Vidal.
     ADMM and Accelerated ADMM as Continuous Dynamical Systems.
     In International Conference on Machine Learning, 2018. arXiv:1805.06579 [math.OC]
     Download: (unavailable)


122. S. Mahendran, H. Ali, and R. Vidal.
     A mixed classification-regression framework for 3D pose estimation from 2D images.
     In British Machine Vision Conference, 2018.
     Download: [pdf] [poster] [slides] 


123. S. Mahendran, H. Ali, and R. Vidal.
     Convolutional Networks for Object Category and 3D Pose Estimation from 2D Images.
     In European Conference on Computer Vision, 2018.
     Download: [pdf] [poster] [slides] 


124. E. Mavroudi, D. Bhaskara, S. Sefati, H. Ali, and R. Vidal.
     End-to-End Fine-Grained Action Segmentation and Recognition Using Conditional Random Field Models and Discriminative Sparse Coding.
     In IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
     Download: [pdf] [HTML] 


125. Poorya Mianjy, Raman Arora, and René Vidal.
     On the implicit bias of dropout.
     In International Conference on Machine Learning, 2018.
     Download: [pdf] [HTML] 


126. Carolina Pacheco and René Vidal.
     Recurrent Neural Networks for Classifying Human Embryonic Stem Cell-Derived Cardiomyocytes.
     In Medical Image Computing and Computer Assisted Intervention, pp. 581–589, 2018.
     Download: [pdf] [poster] 


127. Manolis C. Tsakiris and René Vidal.
     Theoretical Analysis of Sparse Subspace Clustering with Missing Entries.
     In International Conference on Machine Learning, pp. 4975–4984, 2018.
     Download: [pdf] 


128. Florence Yellin, Benjamin D Haeffele, and Rene Vidal.
     Multi-Cell Classification by Convolutional Dictionary Learning with Class Proportion Priors.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 8953–8961, 2018.
     Download: [pdf] 


129. Chong You, Chi Li, Daniel P. Robinson, and René Vidal.
     A Scalable Exemplar-based Subspace Clustering Algorithm for Class-Imbalanced Data.
     In European Conference on Computer Vision, 2018.
     Download: [pdf] 


130. Mengnan Zhao, M. Devrim Kaba, René Vidal, Daniel P. Robinson, and Enrique Mallada.
     Sparse Recovery over Graph Incidence Matrices.
     In 57th IEEE Conference on Decision and Control (CDC), 12 2018.
     Download: [pdf] [HTML] 


131. Z. Zhu, Y. Wang, D. P. Robinson, D. Naiman, R. Vidal, and M. C. Tsakiris.
     Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms.
     In Neural Information Processing Systems, 2018.
     Download: [pdf] [HTML] 


2017
132. B.D. Haeffele, R. Stahl, G. Vanmeerbeeck, and R. Vidal.
     Efficient Reconstruction of Holographic Lens-Free Images by Sparse Phase Recovery.
     In Medical Image Computing and Computer Assisted Intervention, pp. 109–117, 2017.
     Download: [HTML] [poster] 


133. Benjamin D Haeffele, Sophie Roth, Lin Zhou, and Rene Vidal.
     Removal of the Twin Image Artifact in Holographic Lens-Free Imaging by Sparse Dictionary Learning and Coding.
     In IEEE International Symposium on Biomedical Imaging, pp. 741–744, 2017.
     Download: [pdf] [HTML] 


134. Benjamin D Haeffele and Rene Vidal.
     Global Optimality in Neural Network Training.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 7331–7339, 2017.
     Download: [pdf] [HTML] [slides] 


135. C. Lea, M. Flynn, R. Vidal, A. Reiter, and G. Hager.
     Temporal Convolutional Networks for Action Segmentation and Detection.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2017.
     Download: [pdf] 


136. S. Mahendran, H. Ali, and R. Vidal.
     3D Pose Regression using Convolutional Neural Networks.
     In IEEE International Conference on Computer Vision Workshop on Recovering 6D Object Pose, 2017.
     Download: [pdf] [poster] [slides] 


137. E. Mavroudi, L. Tao, and R. Vidal.
     Deep Moving Poselets for Video Based Action Recognition.
     In IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 111–120, 2017.
     Download: [pdf] [HTML] 


138. P. Morerio, J. Cavazza, R. Volpi, René Vidal, and Vittorio Murino.
     Curriculum Dropout.
     In IEEE International Conference on Computer Vision, Oct 2017.
     Download: [pdf] [HTML] 


139. E. Schwab, R. Vidal, and N. Charon.
     ($k, q$)-Compressed Sensing for dMRI with Joint Spatial-Angular Sparsity Prior.
     In MICCAI Workshop on Computational Diffusion MRI, 2017.
     Download: [pdf] 


140. M. C. Tsakiris and R. Vidal.
     Hyperplane clustering via dual principal component pursuit.
     In International Conference on Machine Learning, 2017.
     Download: [pdf] 


141. Florence Yellin, Benjamin D Haeffele, and Rene Vidal.
     Blood Cell Detection and Counting in Holographic Lens-free Imaging by Convolutional Sparse Dictionary Learning and Coding.
     In IEEE International Symposium on Biomedical Imaging, pp. 650–653, 2017.
     Download: [pdf] [HTML] 


142. Chong You, Daniel P. Robinson, and René Vidal.
     Provable Self-Representation Based Outlier Detection in a Union of Subspaces.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 4323–4332, 2017.
     Download: [pdf] 


2016
143. C. Lea, A. Reiter, R. Vidal, and G. D. Hager.
     Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation.
     In European Conference on Computer Vision, 2016.
     Download: [pdf] 


144. C. Lea, R. Vidal, A. Reiter, and G. D. Hager.
     Temporal Convolutional Networks: A Unified Approach to Action Segmentation.
     In Workshop on Brave New Ideas on Motion Representation, 2016.
     Download: [pdf] 


145. C. Lea, R. Vidal, and G. D. Hager.
     Learning Convolutional Action Primitives for Fine-grained Action Recognition.
     In IEEE International Conference on Robotics and Automation, 2016.
     Download: [pdf] 


146. E. Schwab, R. Vidal, and N. Charon.
     Thinking Outside the Voxel: A Joint Spatial-Angular Basis for Sparse Whole Brain HARDI Reconstruction.
     In International Society for Magnetic Resonance in Medicine (ISMRM), 2016.
     Download: [HTML] 


147. E. Schwab, R. Vidal, H. E. Cetingül, and M. Nadar.
     Using A Hyperspherical Harmonic Basis for Sparse Multi-Voxel Modeling of Diffusion MRI.
     In International Society for Magnetic Resonance in Medicine (ISMRM), 2016.
     Download: [HTML] 


148. E. Schwab, R. Vidal, and N. Charon.
     Spatial-Angular Sparse Coding for HARDI.
     In Medical Image Computing and Computer Assisted Intervention, pp. 475–483, 2016.
     Download: [pdf] [HTML] [poster] [slides] 


149. Chong You, Claire Donnat, Daniel P. Robinson, and René Vidal.
     A Divide-and-Conquer Framework for Large-Scale Subspace Clustering.
     In Asilomar Conference on Signals, Systems and Computers, 2016.
     Download: [pdf] 


150. Chong You, Chun-Guang Li, Daniel P. Robinson, and René Vidal.
     Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 3928–3937, 2016.
     Download: [pdf] 


151. Chong You, Daniel P. Robinson, and René Vidal.
     Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 3918–3927, 2016.
     Download: [pdf] 


2015
152. B. Afsari and R. Vidal.
     Model Order Reduction for Discrete-Time LTI Systems Using the Alignment Distance.
     In American Control Conference, 2015.
     Download: [pdf] 


153. G. Gorospe, R. Zhu, J. Q. He, L. Tung, L. Younes, and R. Vidal.
     Efficient Metamorphosis Computation for Classifying Embryonic Cardiac Action Potentials.
     In MICCAI Workshop on the Mathematical Foundations in Computational Anatomy, 2015.
     Download: [pdf] 


154. C. Lea, G. D. Hager, and R. Vidal.
     An Improved Model for Segmentation and Recognition of Fine-Grained Activities with Application to Surgical Training Tasks.
     In IEEE Winter Conference on Applications of Computer Vision, pp. 1123–1129, 2015.
     Download: [pdf] 


155. C.-G. Li and R. Vidal.
     Structured Sparse Subspace Clustering: A Unified Optimization Framework.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 277–286, 2015.
     Download: [HTML] 


156. C.-G. Li, C. You, and R. Vidal.
     On Sufficient Conditions for Affine Sparse Subspace Clustering.
     In Signal Processing with Adaptive Sparse Structured Representations, 2015.
     Download: [pdf] 


157. E. Schwab, M. A. Yassa, M. Weiner, and R. Vidal.
     Using Automatic HARDI Feature Selection, Registration, and Atlas Building to Characterize the Neuroanatomy of Beta-Amyloid Pathology.
     In MICCAI Workshop on Computational Diffusion MRI, 2015.
     Download: [pdf] [poster] [slides] 


158. S. Sefati, N. J. Cowan, and R. Vidal.
     Linear Systems with Sparse Inputs: Observability and Input Recovery.
     In American Control Conference, 2015.
     Download: [pdf] 


159. S. Sefati, N. J. Cowan, and R. Vidal.
     Learning Shared, Discriminative Dictionaries for Surgical Gesture Segmentation and Classification.
     In MICCAI 6th Workshop on Modeling and Monitoring of Computer Assisted Interventions (M2CAI), Munich, Germany, 2015.
     Download: [pdf] 


160. L. Tao and R. Vidal.
     Moving Poselets: A Discriminative and Interpretable Skeletal Motion Representation for Action Recognition.
     In ChaLearn Looking at People Workshop 2015, 2015.
     Download: [pdf] 


161. M.C. Tsakiris and R. Vidal.
     Dual Principal Component Pursuit.
     In ICCV Workshop on Robust Subspace Learning and Computer Vision, pp. 10–18, 2015.
     Download: [pdf] 


162. M.C. Tsakiris and R. Vidal.
     Filtrated Spectral Algebraic Subspace Clustering.
     In ICCV Workshop on Robust Subspace Learning and Computer Vision, pp. 28–36, 2015.
     Download: [pdf] 


163. C. Yang, D. Robinson, and R. Vidal.
     Sparse Subspace Clustering with Missing Entries.
     In International Conference on Machine Learning, 2015.
     Download: [pdf] 


164. Chong You and René Vidal.
     Geometric Conditions for Subspace-Sparse Recovery.
     In International Conference on Machine Learning, pp. 1585–1593, 2015.
     Download: [HTML] [poster] 


165. C. You and R. Vidal.
     Geometric Conditions for Subspace-Sparse Recovery.
     In Signal Processing with Adaptive Sparse Structured Representations, 2015.
     Download: [pdf] 


2014
166. Benjamin D Haeffele, Eric Young, and Rene Vidal.
     Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing.
     In International Conference on Machine Learning, pp. 2007–2015, 2014.
     Download: [pdf] 


167. V. M. Patel and R. Vidal.
     Kernel Sparse Subspace Clustering.
     In IEEE International Conference on Image Processing, pp. 2849–2853, 2014.
     Download: [HTML] 


168. L. Tao, F. Porikli, and R. Vidal.
     Sparse Dictionaries for Semantic Segmentation.
     In European Conference on Computer Vision, 2014.
     Download: [pdf] [HTML] 


169. M. C. Tsakiris and R. Vidal.
     Abstract Algebraic-Geometric Subspace Clustering.
     In Asilomar Conference on Signals, Systems and Computers, 2014.
     Download: [pdf] 


170. S. Wolfers, E. Schwab, and R. Vidal.
     Nonnegative ODF Estimation Via Optimal Constraint Selection.
     In IEEE International Symposium on Biomedical Imaging, pp. 734–737, 2014.
     Download: [pdf] [HTML] [poster] 


2013
171. B. Afsari and R. Vidal.
     The Alignment Distance on Spaces of Linear Dynamical Systems.
     In IEEE Conference on Decision and Control, 2013.
     Download: [pdf] 


172. B. Afsari and R. Vidal.
     Group Action Induced Distances on Spaces of High-Dimensional Linear Stochastic Processes.
     In Geometric Science of Information, pp. 425–432, LNCS 8085, 2013.
     Download: [pdf] 


173. N. Ahmidi, Y. Gao, B. Bejar, S. Vedula, S. Khudanpur, R. Vidal, and G. Hager.
     String Motif-Based Description of Tool Motion for Detecting Skill and Gestures in Robotic Surgery.
     In Medical Image Computing and Computer Assisted Intervention, 2013.
     Download: [HTML] 


174. R. Chaudhry and R. Vidal.
     Initial-State Invariant Binet-Cauchy Kernels for the Comparison of Linear Dynamical Systems.
     In IEEE Conference on Decision and Control, 2013.
     Download: [pdf] [HTML] 


175. R. Chaudhry, F. Ofli, G. Kurillo, R. Bajcsy, and R. Vidal.
     Bio-inspired Dynamic 3D Discriminative Skeletal Features for Human Action Recognition.
     In International Workshop on Human Activity Understanding from 3D Data, 2013.
     Download: [pdf] 


176. G. Gorospe, L. Younes, L. Tung, and R. Vidal.
     A Metamorphosis Distance for Embryonic Cardiac Action Potential Interpolation and Classification.
     In Medical Image Computing and Computer Assisted Intervention, pp. 469–476, 2013.
     Download: [pdf] [HTML] 


177. A. Jain, S. Chatterjee, and R. Vidal.
     Coarse-to-fine Semantic Video Segmentation using Supervoxel Trees.
     In IEEE International Conference on Computer Vision, 2013.
     Download: [pdf] 


178. N. D. Jimenez, B. Afsari, and R. Vidal.
     Fast Jacobi-type Algorithm for Computing Distances Between Linear Dynamical Systems.
     In European Control Conference, pp. 3682 – 3687, 2013.
     Download: [pdf] 


179. H-A. Lobel, A. Soto, and R. Vidal.
     Hierarchical Joint Max-Margin Learning of Mid and Top Level Representations for Visual Recognition.
     In IEEE International Conference on Computer Vision, 2013.
     Download: [pdf] 


180. H-A. Lobel, R. Vidal, D. Mery, and A. Soto.
     Joint Dictionary and Classifier Learning for Categorization of Images Using a Max-margin Framework.
     In Pacific-Rim Symposium on Image and Video Technology, 2013.
     Download: [pdf] [HTML] 


181. F. Ofli, R. Chaudhry, G. Kurillo, R. Vidal, and R. Bajcsy.
     Berkeley MHAD: A Comprehensive Multimodal Human Action Database.
     In IEEE Workshop on Applications of Computer Vision, 2013.
     Download: [pdf] [HTML] 


182. V. M. Patel, H. V. Nguyen, and R. Vidal.
     Latent Space Sparse Subspace Clustering.
     In IEEE International Conference on Computer Vision, pp. 225–232, 2013.
     Download: [pdf] 


183. E. Schwab, H. E. Cetingül, B. Afsari, M. A. Yassa, and R. Vidal.
     Rotation Invariant Features for HARDI.
     In Information Processing in Medical Imaging, pp. 322–330, 2013.
     Download: [pdf] [HTML] [poster] 


184. L. Tao, L. Zappella, G. Hager, and R. Vidal.
     Segmentation and Recognition of Surgical Gestures from Kinematic and Video Data.
     In Medical Image Computing and Computer Assisted Intervention, 2013.
     Download: [pdf] [HTML] 


185. E. Yoruk and R. Vidal.
     A 3D Wireframe Model for Efficient Object Localization and Pose Estimation.
     In ICCV Workshop on 3D Representation and Recognition, 2013.
     Download: [pdf] 


2012
186. B. Afsari, R. Chaudhry, A. Ravichandran, and R. Vidal.
     Group Action Induced Distances for Averaging and Clustering Linear Dynamical Systems with Applications to the Analysis of Dynamic Visual Scenes.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2012.
     Download: [pdf] [HTML] 


187. Benjamín Béjar, Luca Zappella, and René Vidal.
     Surgical Gesture Classification from Video Data.
     In Medical Image Computing and Computer Assisted Intervention, pp. 34–41, 2012.
     Download: [pdf] [HTML] 


188. H. E. Cetingül, B. Afsari, and R. Vidal.
     An Algebraic Solution to Rotation Recovery in HARDI from Correspondences of Orientation Distribution Functions.
     In IEEE International Symposium on Biomedical Imaging, 2012.
     Download: [pdf] [HTML] 


189. H. E. Cetingül, B. Afsari, M. Wright, P. Thompson, and R. Vidal.
     Group action induced averaging for HARDI processing.
     In IEEE International Symposium on Biomedical Imaging, 2012.
     Download: [pdf] [HTML] 


190. E. Elhamifar, G. Sapiro, and R. Vidal.
     See All by Looking at A Few: Sparse Modeling for Finding Representative Objects.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2012.
     Download: [pdf] 


191. E. Elhamifar, G. Sapiro, and R. Vidal.
     Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery.
     In Neural Information Processing and Systems, 2012.
     Download: [pdf] 


192. A. Jain, L. Zappella, P. McClure, and R. Vidal.
     Visual Dictionary Learning for Joint Object Categorization and Segmentation.
     In European Conference on Computer Vision, 2012.
     Download: [pdf] 


193. F. Ofli, R. Chaudhry, G. Kurillo, R. Vidal, and R. Bajcsy.
     Sequence of the Most Informative Joints (SMIJ): A New Representation for Human Skeletal Action Recognition.
     In International Workshop on Human Activity Understanding from 3D Data, 2012.
     Download: [pdf] 


194. D. Perrone, A. Ravichandran, R. Vidal, and P. Favaro.
     Image Priors for Image Deblurring with Uncertain Blur.
     In British Machine Vision Conference, 2012.
     Download: (unavailable)


195. E. Schwab, B. Afsari, and R. Vidal.
     Estimation of Non-Negative ODFs using Eigenvalue Distribution of Spherical Functions.
     In Medical Image Computing and Computer Assisted Intervention, pp. 322–330, 7511, 2012.
     Download: [pdf] [HTML] [poster] 


196. L. Tao, E. Elhamifar, S. Khudanpur, G. Hager, and R. Vidal.
     Sparse Hidden Markov Models for Surgical Gesture Classification and Skill Evaluation.
     In Information Processing in Computed Assisted Interventions, 2012.
     Download: [pdf] 


197. R. Tron, B. Afsari, and R. Vidal.
     Intrinsic Consensus on $SO(3)$ with Almost-Global Convergence.
     In IEEE Conference on Decision and Control, 2012.
     Download: [pdf] [HTML] 


2011
198. H. E. Cetingül and R. Vidal.
     Sparse Riemannian Manifold Clustering for HARDI Segmentation.
     In IEEE International Symposium on Biomedical Imaging, pp. 839–842, 2011.
     Download: [pdf] [HTML] 


199. Y. Chen, R. Tron, A. Terzis, and R. Vidal.
     Accelerated Corrective Consensus: Convergence to the Exact Average at a Faster Rate.
     In American Control Conference, 2011.
     Download: [pdf] 


200. Y. Chen, R. Tron, A. Terzis, and R. Vidal.
     Corrective Consensus with Asymmetric Wireless Links.
     In IEEE Conference on Decision and Control, 2011.
     Download: (unavailable)


201. E. Elhamifar and R. Vidal.
     Sparsity in Unions of Subspaces for Classification and Clustering of High-Dimensional Data.
     In Allerton Conference on Communication, Control, and Computing, 2011.
     Download: (unavailable)


202. E. Elhamifar and R. Vidal.
     Robust Classification using Structured Sparse Representation.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2011.
     Download: [pdf] 


203. E. Elhamifar and R. Vidal.
     Sparse Manifold Clustering and Embedding.
     In Neural Information Processing and Systems, 2011.
     Download: [pdf] 


204. Paolo Favaro, René Vidal, and Avinash Ravichandran.
     A Closed Form Solution to Robust Subspace Estimation and Clustering.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 1801 –1807, 2011.
     Download: [pdf] 


205. D. Rother and R. Vidal.
     A Hypothesize-and-Bound Algorithm for Simultaneous Object Classification, Pose Estimation and 3D Reconstruction from a Single 2D Image.
     In ICCV Workshop on 3D Representation and Recognition, 2011.
     Download: [pdf] 


206. D. Singaraju and R. Vidal.
     Using Global Bag of Features Models in Random Fields for Joint Categorization and Segmentation of Objects.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2011.
     Download: [pdf] [HTML] 


207. R. Tron, B. Afsari, and R. Vidal.
     Average Consensus on Riemannian Manifolds with Bounded Curvature.
     In IEEE Conference on Decision and Control, 2011.
     Download: (unavailable)


208. R. Tron and R. Vidal.
     Distributed Computer Vision Algorithms Through Distributed Averaging.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2011.
     Download: [pdf] 


2010
209. Y. Chen, R. Tron, A. Terzis, and R. Vidal.
     Corrective Consensus: Converging to the Exact Average.
     In IEEE Conference on Decision and Control, 2010.
     Download: [HTML] 


210. E. Elhamifar and R. Vidal.
     Clustering Disjoint Subspaces via Sparse Representation.
     In IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 1926–1929, 2010.
     Download: [HTML] 


211. F. Lauer, G. Bloch, and R. Vidal.
     Nonlinear Hybrid System Identification with Kernel Models.
     In IEEE Conference on Decision and Control, 2010.
     Download: [HTML] 


212. J. Li, E. Elhamifar, I-J Wang, and R. Vidal.
     Consensus with Robustness to Outliers via Distributed Optimization.
     In IEEE Conference on Decision and Control, 2010.
     Download: [HTML] 


213. A. Ravichandran, P. Favaro, and R. Vidal.
     A Unified Approach to Segmentation and Categorization of Dynamic Textures.
     In Asian Conference on Computer Vision, 2010.
     Download: [pdf] 


2009
214. L. Bako, G. Mercere, R. Vidal, and S. Lecoeuche.
     Identification of Switched Linear State Space Models without Dwell Time.
     In IFAC Symposium on System Identification, 2009.
     Download: [HTML] 


215. H. E. Cetingül and R. Vidal.
     Intrinsic Mean Shift for Clustering on Stiefel and Grassmann Manifolds.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2009.
     Download: [HTML] 


216. H. E. Cetingül, G. Plank, N. Trayanova, and R. Vidal.
     Estimation of Multimodal Orientation Distribution Functions from Cardiac MRI For Tracking Purkinje fibers through branchings.
     In IEEE International Symposium on Biomedical Imaging, pp. 839–842, 2009.
     Download: [HTML] 


217. H. E. Cetingül, G. Plank, N. Trayanova, and R. Vidal.
     Stochastic Tractography in 3-D Images via Nonlinear Filtering and Spherical Clustering.
     In Workshop on Probabilistic Models for Medical Image Analysis, 2009.
     Download: [pdf] 


218. R. Chaudhry, A. Ravichandran, G. Hager, and R. Vidal.
     Histograms of Oriented Optical Flow and Binet-Cauchy Kernels on Nonlinear Dynamical Systems for the Recognition of Human Actions.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2009.
     Download: [HTML] 


219. E. Elhamifar, M. Petreczky, and R. Vidal.
     Rank Tests for the Observability of Discrete-Time Jump Linear Systems with Inputs.
     In American Control Conference, 2009.
     Download: [pdf] 


220. Ehsan Elhamifar and René Vidal.
     Sparse Subspace Clustering.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 2790–2797, 2009.
     Download: [HTML] 


221. E. Elhamifar and R. Vidal.
     Distributed Calibration of Camera Sensor Networks.
     In International Conference on Distributed Smart Cameras, 2009.
     Download: [HTML] 


222. A. Goh, C. Lenglet, P.M. Thompson, and R. Vidal.
     A Nonparametric Riemannian Framework for Processing High Angular Resolution Diffusion Images (HARDI).
     In IEEE Conference on Computer Vision and Pattern Recognition, 2009.
     Download: [HTML] 


223. A. Goh, C. Lenglet, P.M. Thompson, and R. Vidal.
     Estimating Orientation Distribution Functions with Probability Density Constraints and Spatial Regularity.
     In Medical Image Computing and Computer Assisted Intervention, pp. 877–885, 5761, 2009.
     Download: [HTML] 


224. F. Lauer, R. Vidal, and G. Bloch.
     A Product-of-Errors Framework for Linear Hybrid System Identification.
     In IFAC Symposium on System Identification, 2009.
     Download: [HTML] 


225. A. Ravichandran, R. Chaudhry, and R. Vidal.
     View-Invariant Dynamic Texture Recognition using a Bag of Dynamical Systems.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2009.
     Download: [HTML] 


226. D. Singaraju, L. Grady, and R. Vidal.
     P-Brush: Continuous Valued MRFs with Normed Pairwise Distributions for Image Segmentation.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2009.
     Download: [HTML] 


227. R. Tron and R. Vidal.
     Distributed Image-Based 3-D Localization in Camera Sensor Networks.
     In IEEE Conference on Decision and Control, 2009.
     Download: [HTML] 


2008
228. Laurent Bako and René Vidal.
     Algebraic Identification of MIMO SARX Models.
     In Hybrid Systems: Computation and Control, pp. 43–57, Spinger-Verlag, 2008.
     Download: [pdf] 


229. H. E. Cetingül, R. Vidal, G. Plank, and N. Trayanova.
     Nonlinear Filtering for Extracting Orientation and Tracing Tubular Structures in 2-D Medical Images.
     In IEEE International Symposium on Biomedical Imaging, pp. 260–263, 2008.
     Download: [pdf] 


230. A. Goh and R. Vidal.
     Clustering and Dimensionality Reduction on Riemannian Manifolds.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2008.
     Download: [pdf] 


231. A. Goh and R. Vidal.
     Segmenting Fiber Bundles in Diffusion Tensor Images.
     In European Conference on Computer Vision, pp. 238–250, 2008.
     Download: [pdf] 


232. A. Goh and R. Vidal.
     Unsupervised Riemannian Clustering of Probability Density Functions.
     In European Conference on Machine Learning, 2008.
     Download: [pdf] 


233. R. Hartley and R. Vidal.
     Perspective Nonrigid Shape and Motion Recovery.
     In European Conference on Computer Vision, 2008.
     Download: [pdf] 


234. M. Petreczky and R. Vidal.
     Realization of Discrete-Time Semi-Algebraic Hybrid Systems.
     In Hybrid Systems: Computation and Control, Springer Verlag, 2008.
     Download: [pdf] 


235. S. Rao, R. Tron, Y. Ma, and R. Vidal.
     Motion Segmentation via Robust Subspace Separation in the Presence of Outlying, Incomplete, or Corrupted Trajectories.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2008.
     Download: [pdf] 


236. A. Ravichandran and R. Vidal.
     Video Registration using Dynamic Textures.
     In European Conference on Computer Vision, 2008.
     Download: [pdf] 


237. D. Singaraju, L. Grady, and R. Vidal.
     Interactive Image Segmentation Via Minimization of Quadratic Energies on Directed Graphs.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2008.
     Download: [pdf] 


238. D. Singaraju and R. Vidal.
     Interactive Image Matting for Multiple Layers.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2008.
     Download: [pdf] 


239. R. Tron, R. Vidal, and A. Terzis.
     Distributed pose averaging in camera networks via consensus on SE(3).
     In International Conference on Distributed Smart Cameras, 2008.
     Download: [pdf] 


240. R. Tron and R. Vidal.
     Distributed Face Recognition via Consensus on SE(3).
     In Workshop on Omnidirectional Vision, 2008.
     Download: [pdf] 


2007
241. H. E. Cetingül, R. Chaudhry, and R. Vidal.
     A System Theoretic Approach to Synthesis and Classification of Lip Articulation.
     In International Workshop on Dynamical Vision, 2007.
     Download: [pdf] 


242. A. Ghoreyshi and R. Vidal.
     Epicardial Segmentation in Dynamic Cardiac MR Sequences Using Priors on Shape, Intensity, and Dynamics, in a Level Set Framework.
     In IEEE International Symposium on Biomedical Imaging, pp. 860–863, 2007.
     Download: [pdf] 


243. A. Goh and R. Vidal.
     Segmenting Motions of Different Types by Unsupervised Manifold Clustering.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–6, 2007.
     Download: [pdf] 


244. T. Li, V. Kallem, D. Singaraju, and R. Vidal.
     Projective Factorization of Multiple Rigid-Body Motions.
     In IEEE Conference on Computer Vision and Pattern Recognition, 2007.
     Download: [pdf] 


245. M. Petreczky and R. Vidal.
     Realization Theory for Stochastic Jump-Markov Linear Systems.
     In IEEE Conference on Decision and Control, 2007.
     Download: [pdf] 


246. M. Petreczky and R. Vidal.
     Metrics and topology for nonlinear and hybrid systems.
     In Hybrid Systems: Computation and Control, Springer Verlag, 2007.
     Download: [pdf] 


247. A. Ravichandran and R. Vidal.
     Mosaicing Nonrigid Dynamical Scenes.
     In International Workshop on Dynamic Vision, 2007.
     Download: [pdf] 


248. Roberto Tron and René Vidal.
     A Benchmark for the Comparison of 3-D Motion Segmentation Algorithms.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8, 2007.
     Download: [pdf] 


249. R. Vidal and P. Favaro.
     DynamicBoost: Boosting Time Series Generated by Dynamical Systems.
     In IEEE International Conference on Computer Vision, 2007.
     Download: [pdf] 


250. R. Vidal.
     Identification of Spatial-Temporal Hybrid Systems.
     In IEEE Conference on Decision and Control, 2007.
     Download: [pdf] 


251. R. Vidal, S. Soatto, and A. Chiuso.
     Applications of Hybrid System Identification in Computer Vision.
     In European Control Conference, 2007.
     Download: [pdf] 


2006
252. A. Ghoreyshi and R. Vidal.
     Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets.
     In International Workshop on Dynamic Vision, pp. 127–141, LNCS 4358, 2006.
     Download: [pdf] 


253. A. Goh and R. Vidal.
     Algebraic Methods for Direct and Feature Based Registration of Diffusion Tensor Images.
     In European Conference on Computer Vision, pp. 514–525, 2006.
     Download: [pdf] 


254. A. Goh and R. Vidal.
     An Algebraic Solution to Rigid Registration of Diffusion Tensor Images.
     In IEEE International Symposium on Biomedical Imaging, pp. 642–645, 2006.
     Download: [pdf] 


255. L. Lu and R. Vidal.
     Combined Central and Subspace Clustering on Computer Vision Applications.
     In International Conference on Machine Learning, pp. 593–600, 2006.
     Download: [pdf] 


256. A. Ravichandran, R. Vidal, and H. Halperin.
     Segmenting a Beating Heart Using PolySegment and Spatial GPCA.
     In IEEE International Symposium on Biomedical Imaging, pp. 634–637, 2006.
     Download: [pdf] 


257. D. Singaraju and R. Vidal.
     A Bottom up Algebraic Approach to Motion Segmentation.
     In Asian Conference on Computer Vision, pp. 286–296, 1, 2006.
     Download: [pdf] 


258. D. Singaraju and R. Vidal.
     Direct Segmentation of Multiple Motion Models of Different Types.
     In International Workshop on Dynamical Vision, 2006.
     Download: [pdf] 


259. R. Vidal and D. Abretske.
     Nonrigid Shape and Motion from Multiple Perspective Views.
     In European Conference on Computer Vision, pp. 205–218, 2006.
     Download: [pdf] 


260. R. Vidal.
     Online clustering of moving hyperplanes.
     In Neural Information Processing Systems, NIPS, 2006.
     Download: [pdf] 


2005
261. X. Fan and R. Vidal.
     The Space of Multibody Fundamental Matrices: Rank, Geometry and Projection.
     In International Workshop on Dynamical Vision, pp. 1–17, 2005.
     Download: [pdf] 


262. Y. Hashambhoy and R. Vidal.
     Recursive Identification of Switched ARX Models with Unknown Number of Models and Unknown Orders.
     In IEEE Conference on Decision and Control, pp. 6115–6121, 2005.
     Download: [pdf] 


263. A. Juloski, W. Heemels, G. Ferrari-Trecate, R. Vidal, S. Paoletti, and J. Niessen.
     Comparison of four procedures for the identification of hybrid systems.
     In Hybrid Systems: Computation and Control, LNCS, pp. 354–369, Springer-Verlag, Berlin, 2005.
     Download: [pdf] 


264. Y. Ma and R. Vidal.
     Identification of Deterministic Switched ARX Systems via Identification of Algebraic Varieties.
     In Hybrid Systems: Computation and Control, pp. 449–465, Springer Verlag, 2005.
     Download: [pdf] 


265. R. Vidal and A. Ravichandran.
     Optical Flow Estimation and Segmentation of Multiple Moving Dynamic Textures.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 516–521, II, 2005.
     Download: [pdf] 


266. R. Vidal and D. Singaraju.
     A Closed-Form Solution to Direct Motion Segmentation.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 510–515, II, 2005.
     Download: [pdf] 


267. R. Vidal.
     Multi-Subspace Methods for Motion Segmentation from Affine, Perspective and Central Panoramic Cameras.
     In IEEE Conference on Robotics and Automation, pp. 1753–1758, 2005.
     Download: [pdf] 


2004
268. R. Hartley and R. Vidal.
     The Multibody Trifocal Tensor: Motion Segmentation from 3 Perspective Views.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 769–775, I, 2004.
     Download: [pdf] 


269. K. Huang, Y. Ma, and R. Vidal.
     Minimum Effective Dimension for Mixtures of Subspaces: A Robust GPCA, Algorithm and its Applications.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 631–638, II, 2004.
     Download: [pdf] 


270. D. Mery, F. Ochoa, and R. Vidal.
     Tracking of Points in a Calibrated and Noisy Image Sequence.
     In International Conference on Image Analysis and Recognition, 2004.
     Download: [pdf] 


271. René Vidal.
     Identification of PWARX Hybrid Models with Unknown and Possibly Different Orders.
     In American Control Conference, pp. 547–552, 2004.
     Download: [pdf] 


272. R. Vidal and B.D.O. Anderson.
     Recursive Identification of Switched ARX Hybrid Models: Exponential Convergence and Persistence of Excitation.
     In IEEE Conference on Decision and Control, pp. 32–37, 2004.
     Download: [pdf] 


273. R. Vidal, Y. Ma, and J. Piazzi.
     A New GPCA Algorithm for Clustering Subspaces by Fitting, Differentiating and Dividing Polynomials.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 510–517, I, 2004.
     Download: [pdf] 


274. R. Vidal and R. Hartley.
     Motion Segmentation with Missing Data by PowerFactorization and Generalized PCA.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 310–316, II, 2004.
     Download: [pdf] 


275. R. Vidal and Y. Ma.
     A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation.
     In European Conference on Computer Vision, pp. 1–15, 2004.
     Download: [pdf] 


2003
276. N. Cowan, O. Shakernia, R. Vidal, and S. Sastry.
     Vision-based Follow-the-Leader.
     In IEEE Conference on Intelligent Robotic Systems, 2003.
     Download: [pdf] 


277. O. Shakernia, R. Vidal, and S. Sastry.
     Multi-Body Motion Estimation and Segmentation From Multiple Central Panoramic Views.
     In IEEE International Conference on Robotics and Automation, pp. 571–576, 1, 2003.
     Download: [pdf] 


278. O. Shakernia, R. Vidal, and S. Sastry.
     Omnidirectional vision-based egomotion estimation from backprojection flow.
     In Workshop on Omnidirectional Vision, 2003.
     Download: [pdf] 


279. O. Shakernia, R. Vidal, and S. Sastry.
     Structure from small baseline motion with central panoramic cameras.
     In Workshop on Omnidirectional Vision, 2003.
     Download: [pdf] 


280. R. Vidal, S. Soatto, Y. Ma, and S. Sastry.
     An Algebraic Geometric Approach to the Identification of a Class of Linear Hybrid Systems.
     In IEEE Conference on Decision and Control, pp. 167–172, 2003.
     Download: [pdf] 


281. R. Vidal, Y. Ma, and S. Sastry.
     Generalized Principal Component Analysis (GPCA).
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 621–628, I, 2003.
     Download: [pdf] 


282. R. Vidal and S. Sastry.
     Optimal Segmentation of Dynamic Scenes from Two Perspective Views.
     In IEEE Conference on Computer Vision and Pattern Recognition, pp. 281–286, 2, 2003.
     Download: [pdf] 


283. R. Vidal, A. Chiuso, S. Soatto, and S. Sastry.
     Observability of Linear Hybrid Systems.
     In Hybrid Systems: Computation and Control, pp. 526–539, Springer Verlag, 2003.
     Download: [pdf] 


284. R. Vidal, O. Shakernia, and S. Sastry.
     Formation Control of Nonholonomic Mobile Robots with OmnidirectionalVisual Servoing and Motion Segmentation.
     In IEEE International Conference on Robotics and Automation, pp. 584–589, 1, 2003.
     Download: [pdf] 


2002
285. O. Shakernia, R. Vidal, and S. Sastry.
     Infinitesimal Motion Estimation from Multiple Central Panoramic Views.
     In IEEE Workshop on Motion and Video Computing, pp. 229–234, 2002.
     Download: [pdf] 


286. O. Shakernia, R. Vidal, C. Sharp, Y. Ma, and S. Sastry.
     Multiple View Motion Estimation and Control for Landing an Unmanned Aerial Vehicle.
     In IEEE International Conference on Robotics and Automation, pp. 2793–2798, 2002.
     Download: [pdf] 


287. R. Vidal, S. Soatto, and S. Sastry.
     A Factorization Method for Multibody Motion Estimation and Segmentation.
     In Fortieth Annual Allerton Conference on Communication, Control and Computing, pp. 1625–1634, 2002.
     Download: (unavailable)


288. R. Vidal, O. Shakernia, and S. Sastry.
     Omnidirectional Vision-Based Formation Control.
     In Fortieth Annual Allerton Conference on Communication, Control and Computing, pp. 1625–1634, 2002.
     Download: [pdf] 


289. R. Vidal, A. Chiuso, and S. Soatto.
     Observability and Identifiability of Jump Linear Systems.
     In IEEE Conference on Decision and Control, pp. 3614–3619, 2002.
     Download: [pdf] 


290. R. Vidal, S. Soatto, Y. Ma, and S. Sastry.
     Segmentation of Dynamic Scenes from the Multibody Fundamental Matrix.
     In ECCV Workshop on Visual Modeling of Dynamic Scenes, 2002.
     Download: [pdf] 


291. R. Vidal and J. Oliensis.
     Structure from planar motions with small baselines.
     In European Conference on Computer Vision, pp. 383–398, 2002.
     Download: [pdf] 


292. R. Vidal and S. Sastry.
     Vision based detection of multiple autonomous vehicles for pursuit-evasion games.
     In IFAC World Congress on Automatic Control, 2002.
     Download: [pdf] 


293. R. Vidal and S. Sastry.
     Segmentation of Dynamic Scenes from Image Intensities.
     In IEEE Workshop on Motion and Video Computing, pp. 44–49, 2002.
     Download: [pdf] 


2001
294. H.J. Kim, R. Vidal, D. Shim, O. Shakernia, and S. Sastry.
     A hierarchical approach to Probabilistic Pursuit-Evasion games with unmanned ground and aerial vehicles.
     In IEEE Conference on Decision and Control, pp. 1243–1248, 2001.
     Download: [pdf] 


295. R. Vidal, S. Schaffert, O. Shakernia, J. Lygeros, and S. Sastry.
     Decidable and Semi-decidable Controller Synthesis for Classes of Discrete Time Hybrid Systems.
     In IEEE Conference on Decision and Control, pp. 1243–1278, 2001.
     Download: [pdf] 


296. R. Vidal, Y. Ma, S. Hsu, and S. Sastry.
     Optimal Motion Estimation from the Multiview Normalized Epipolar Constraint.
     In IEEE International Conference on Computer Vision, pp. 34–41, 1, 2001.
     Download: [pdf] 


297. R. Vidal, S. Rashid, C. Sharp, O. Shakernia, H.J. Kim, and S. Sastry.
     Pursuit-Evasion games with unmanned ground and aerial vehicles.
     In IEEE International Conference on Robotics and Automation, pp. 2948–2955, 2001.
     Download: [pdf] 


2000
298. Y. Ma, R. Vidal, J. Kosecká, and S. Sastry.
     Kruppa's Equations Revisited: its Degeneracy, Renormalization and Relations to Chirality.
     In European Conference on Computer Vision, pp. 561–577, 2, 2000.
     Download: [pdf] 


299. R. Vidal, S. Schaffert, J. Lygeros, and S. Sastry.
     Controlled Invariance of Discrete Time Systems.
     In Hybrid Systems: Computation and Control, pp. 437–451, Springer Verlag, 2000.
     Download: [pdf] 


1998
300. R. Vidal and A. Cipriano.
     A Robotic Classifier of Rocks: an Integration of Artificial Vision and Robotics.
     In IFAC Workshop on Algorithms and Architectures for Real-Time Control, pp. 120–125, 1998.
     Download: (unavailable)


1997
301. R. Vidal and A. Cipriano.
     System for Classifying Rocks by using Artificial Vision and a Robot Arm.
     In IEEE International Symposium on Industrial Electronics, pp. 729–734, 2, 1997.
     Download: (unavailable)


1996
302. A. Cipriano, M. Ramos, R. Vidal, and D. Mery.
     Parallel Processing Systems and their Application to Economic Dispatch with Environmental Constraints.
     In Latin-American Congress on Automatic Control, pp. 115–121, 1996.
     Download: (unavailable)


303. R. Vidal and A. Cipriano.
     The Scorbot ER VII Robot Arm: Description and Applications.
     In Chilean Congress on Automatic Control, pp. 17–22, 1996.
     Download: (unavailable)


Theses
2003
304. R. Vidal.
     Generalized Principal Component Analysis (GPCA): an Algebraic Geometric Approach to Subspace Clustering and Motion Segmentation.
     Ph.D. Thesis, University of California, Berkeley, 2003.
     Download: [pdf] 


2000
305. R. Vidal.
     Controlled Invariance of Discrete Time Hybrid Systems.
     Master's Thesis, University of California at Berkeley,2000.
     Download: [pdf] 


1997
306. R. Vidal.
     Control of a Robot Arm using Fuzzy Logic and Image Processing.
     Master's Thesis, Catholic University of Chile,1997.
     Download: (unavailable)


Patents
2017
307. F. Yellin, B. Haeffele, and R. Vidal.
     System and Methods for Counting Blood Cells Flowing in a Microfluidic Chamber.
     June 2017.
     Download: [HTML] 


308. F. Yellin, B. Haeffele, and R. Vidal.
     System and method for Classification of a Population of Objects by Convolutional Dictionary Learning with Class Proportion Data.
     December 2017.
     Download: [HTML] 


309. F. Yellin, B. Haeffele, and R. Vidal.
     System and Methods for Counting Blood Cells Flowing in a Microfluidic Chamber.
     June 2017.
     Download: [HTML] 


310. F. Yellin, B. Haeffele, and R. Vidal.
     System and method for Classification of a Population of Objects by Convolutional Dictionary Learning with Class Proportion Data.
     December 2017.
     Download: [HTML] 


2016
311. R. Vidal and B. Haeffele.
     System and method for reconstruction of holographic lens-free images by multi-depth sparse phase recovery.
     US Patent WO2018085655A1, June 2016.
     Download: [HTML] 


312. R. Vidal and B. Haeffele.
     System and Method for Removal of Twin Image Artifact in Holographic Lens-free Imaging by Sparse Dictionary Learning.
     US Patent EP3318932A1, June 2016.
     Download: [HTML] 


313. F. Yellin, B. Haeffele, and R. Vidal.
     System and method for object detection in holographic lens-free imaging by convolutional dictionary learning and encoding.
     US Patent WO2018085657A1, August 2016.
     Download: [HTML] 


2015
314. R. Vidal, B. Haeffele, and E. Young.
     System and method for structured low-rank matrix factorization: optimality, algorithm, and applications to image processing.
     US Patent US20160371563A1, 2015.
     Download: [HTML] 


315. R. Vidal, B. Haeffele, and E. Young.
     System and method for structured low-rank matrix factorization: optimality, algorithm, and applications to image processing.
     US Patent US20160371563A1, 2015.
     Download: [HTML] 


2011
316. Dheeraj Singaraju, Martin Wojkowsky, Rene Vidal, Roberto Tron, and Solomon Liu.
     IPhone App for semi-automatic segmentation, cutting and pasting of photos.
     JHU Invention Disclosure, May 2011.
     Download: (unavailable)


317. Dheeraj Singaraju, Martin Wojkowsky, Rene Vidal, Roberto Tron, and Solomon Liu.
     IPhone App for semi-automatic segmentation, cutting and pasting of photos.
     JHU Invention Disclosure, May 2011.
     Download: (unavailable)


2009
318. H. E. Cetingül, H. Tek, and R. Vidal.
     A Multiscale Orientation Detector for Analyzing Local Topology of Tubular Structures.
     US Patent 2009E16562US (Pending), 2009.
     Download: (unavailable)


319. H. E. Cetingül, H. Tek, and R. Vidal.
     A Multiscale Orientation Detector for Analyzing Local Topology of Tubular Structures.
     US Patent 2009E16562US (Pending), 2009.
     Download: (unavailable)


320. R. Vidal and A. Ravichandran.
     System and Method for Registering Video Sequences.
     US Patent 20100260439 A1, 2009.
     Download: [HTML] 


321. R. Vidal and A. Ravichandran.
     System and Method for Registering Video Sequences.
     US Patent 20100260439 A1, 2009.
     Download: [HTML] 


2008
322. L. Grady, D. Singaraju, and R. Vidal.
     System and method for image segmentation using continuous valued MRFs with normed pairwise distributions.
     US Patent US8224093B2, US Patent Application 20100104186, 2008.
     Download: [HTML] 


323. L. Grady, D. Singaraju, and R. Vidal.
     System and method for image segmentation using continuous valued MRFs with normed pairwise distributions.
     US Patent US8224093B2, US Patent Application 20100104186, 2008.
     Download: [HTML] 


Unspecified
2021
324. Benjamín Béjar, Ivan Dokmanic, and René Vidal.
     The fastest $L_1,\infty$ in the west.
     IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.
     Download: (unavailable)


2020
325. G. Franca, M. Jordan, and R. Vidal.
     On Dissipative Symplectic Integration with Applications to Gradient-Based Optimization.
     arXiv:2004.06840 [math.OC], 2020.
     Download: (unavailable)


326. Derek Lim, René Vidal, and Benjamin D Haeffele.
     Doubly Stochastic Subspace Clustering.
     arXiv preprint arXiv:2011.14859, 2020.
     Download: (unavailable)


2019
327. B. D. Haeffele, C. Pick, Z. Lin, E. Mathieu, S. C. Ray, and R. Vidal.
     An Optical Model of Whole Blood for Detecting Platelets in Lens-Free Images.
     In International Workshop on Simulation and Synthesis for Medical Imaging, 2019.
     Download: (unavailable)


328. Daniel P Robinson, Rene Vidal, and Chong You.
     Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis.
     arXiv preprint arXiv:1912.13091, 2019.
     Download: (unavailable)


329. F. Yellin, B. Haeffele, and R. Vidal.
     Joint Holographic Detection and Reconstruction.
     In MICCAI Workshop on Machine Learning in Medical Imaging, 2019.
     Download: (unavailable)


2018
330. Evan Schwab, Benjamin D Haeffele, Nicolas Charon, and Rene Vidal.
     Separable Dictionary Learning with Global Optimality and Applications to Diffusion MRI.
     arXiv preprint arXiv:1807.05595, 2018.
     Download: (unavailable)


2017
331. Jacopo Cavazza, Connor Lane, Benjamin D Haeffele, Vittorio Murino, and Rene Vidal.
     An Analysis of Dropout for Matrix Factorization.
     arXiv preprint arXiv:1710.03487, 2017.
     Download: (unavailable)


2015
332. E. Jahangiri, R. Vidal, L. Younes, and D. Geman.
     Object-Level Generative Models for 3D Scene Understanding.
     In SUNw: Scene Understanding Workshop, 2015.
     Download: (unavailable)


333. Manolis C Tsakiris and René Vidal.
     Dual principal component pursuit.
     In Proceedings of the IEEE International Conference on Computer Vision Workshops, 2015.
     Download: (unavailable)


2014
334. A. Ravichandran, P. Favaro, and R. Vidal.
     A Unified Approach to Segmentation and Categorization of Dynamic Textures.
     International Journal of Computer Vision, (Under Review) 2014.
     Download: (unavailable)


335. D. Rother, S. Schütz, and R. Vidal.
     Hypothesize and Bound: A Computational Focus of Attention Mechanism for Simultaneous N-D Segmentation, Pose Estimation and Classification Using Shape Priors.
     International Journal of Computer Vision, 2014.
     Download: [HTML] 


336. D. Rother, S. Mahendran, and R. Vidal.
     Hypothesize and Bound: A Computational Focus of Attention Mechanism for Simultaneous 3D Shape Reconstruction.
     International Journal of Computer Vision, (Submitted) 2014.
     Download: [HTML] 


2010
337. A. Goh and R. Vidal.
     Locally Linear Manifold Clustering (LLMC).
     Journal of Machine Learning Research, (Submitted) 2010.
     Download: (unavailable)


338. A. Goh, C. Lenglet, P. Thompson, and R. Vidal.
     A Convex Framework for Estimation of Orientation Distribution Functions with Non-negativity Constraints and Spatial Regularity.
     Medical Image Analysis, (Submitted) 2010.
     Download: (unavailable)


339. D. Singaraju, L. Grady, and R. Vidal.
     Image Segmentation with Asymmetric Pairwise Penalties.
     IEEE Transactions on Pattern Analysis and Machine Intelligence, (Submitted) 2010.
     Download: (unavailable)


2002
340. R. Vidal, S. Soatto, and S. Sastry.
     A Factorization Method for 3D Multi-body motion estimation and segmentation.
     Technical Report {UCB/ERL} {M}02/3, UC Berkeley, 2002.
     Download: (unavailable)


341. R. Vidal, S. Sastry, J. Kim, O. Shakernia, and D. Shim.
     The Berkeley Aerial Robot Project (BEAR).
     In Workshop on Aerial Robotics, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1–10, 2002.
     Download: (unavailable)

Generated using a modified version of bib2html.pl (originally written by Patrick Riley ) on Thu Feb 02, 2023 15:10:02