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ORCIDRené Vidal
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- affiliation: The Johns Hopkins University, Department of Biomedical Engineering
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2020 – today
- 2022
[j58]Chong You
, Chi Li, Daniel P. Robinson, René Vidal:
Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces. IEEE Trans. Pattern Anal. Mach. Intell. 44(5): 2698-2711 (2022)- [c184]René Vidal:
Semantic Information Pursuit. IMPROVE 2022: 9 - [c183]Effrosyni Mavroudi, Prashast Bindal, René Vidal:
Actor-Centric Tubelets for Real-Time Activity Detection in Extended Videos. WACV (Workshops) 2022: 172-181 - [i67]Joshua T. Vogelstein, Timothy Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael Platt, Lyle Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang:
Prospective Learning: Back to the Future. CoRR abs/2201.07372 (2022) - [i66]Paris V. Giampouras, Benjamin D. Haeffele, René Vidal:
Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension. CoRR abs/2201.09079 (2022) - [i65]Darshan Thaker, Paris Giampouras, René Vidal:
Reverse Engineering 𝓁p attacks: A block-sparse optimization approach with recovery guarantees. CoRR abs/2203.04886 (2022) - [i64]Liangzu Peng, Manolis C. Tsakiris, René Vidal:
ARCS: Accurate Rotation and Correspondence Search. CoRR abs/2203.14493 (2022) - [i63]Aditya Chattopadhyay, Xi Zhang, David Paul Wipf, Himanshu Arora, René Vidal:
Structured Graph Variational Autoencoders for Indoor Furniture layout Generation. CoRR abs/2204.04867 (2022) - [i62]Danny Weyns, Thomas Bäck, René Vidal, Xin Yao, Ahmed Nabil Belbachir:
The Vision of Self-Evolving Computing Systems. CoRR abs/2204.06825 (2022) - 2021
- [j57]Mustafa Devrim Kaba, Mengnan Zhao, René Vidal, Daniel P. Robinson, Enrique Mallada:
What is the Largest Sparsity Pattern That Can Be Recovered by 1-Norm Minimization? IEEE Trans. Inf. Theory 67(5): 3060-3074 (2021) - [c182]Tianyu Ding, Zhihui Zhu, Manolis C. Tsakiris, René Vidal, Daniel P. Robinson:
Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms. AISTATS 2021: 2944-2952 - [c181]Shangzhi Zhang, Chong You, René Vidal, Chun-Guang Li:
Learning a Self-Expressive Network for Subspace Clustering. CVPR 2021: 12393-12403 - [c180]Benjamin David Haeffele, Chong You, René Vidal:
A Critique of Self-Expressive Deep Subspace Clustering. ICLR 2021 - [c179]Tianyu Ding, Zhihui Zhu, René Vidal, Daniel P. Robinson:
Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach. ICML 2021: 2739-2748 - [c178]Mustafa Devrim Kaba, Chong You, Daniel P. Robinson, Enrique Mallada, René Vidal:
A Nullspace Property for Subspace-Preserving Recovery. ICML 2021: 5180-5188 - [c177]Hancheng Min, Salma Tarmoun, René Vidal, Enrique Mallada:
On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks. ICML 2021: 7760-7768 - [c176]Salma Tarmoun, Guilherme França, Benjamin D. Haeffele, René Vidal:
Understanding the Dynamics of Gradient Flow in Overparameterized Linear models. ICML 2021: 10153-10161 - [i61]Hancheng Min, Salma Tarmoun, René Vidal, Enrique Mallada:
On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks. CoRR abs/2105.06351 (2021) - [i60]Danny Weyns, Thomas Bäck, René Vidal, Xin Yao, Ahmed Nabil Belbachir:
Lifelong Computing. CoRR abs/2108.08802 (2021) - [i59]Yunchen Yang, Xinyue Zhang, Tianjiao Ding, Daniel P. Robinson, René Vidal, Manolis C. Tsakiris:
Boosting RANSAC via Dual Principal Component Pursuit. CoRR abs/2110.02918 (2021) - [i58]Shangzhi Zhang, Chong You, René Vidal, Chun-Guang Li:
Learning a Self-Expressive Network for Subspace Clustering. CoRR abs/2110.04318 (2021) - 2020
- [j56]Hans Lobel, René Vidal, Alvaro Soto:
CompactNets: Compact Hierarchical Compositional Networks for Visual Recognition. Comput. Vis. Image Underst. 191: 102841 (2020) - [j55]Joan Bruna, Eldad Haber, Gitta Kutyniok, Thomas Pock, René Vidal:
Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science. J. Math. Imaging Vis. 62(3): 277-278 (2020) - [j54]Benjamin D. Haeffele, René Vidal:
Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications. IEEE Trans. Pattern Anal. Mach. Intell. 42(6): 1468-1482 (2020) - [j53]Xiao Li, Zhihui Zhu, Anthony Man-Cho So, René Vidal:
Nonconvex Robust Low-Rank Matrix Recovery. SIAM J. Optim. 30(1): 660-686 (2020) - [c175]Tianjiao Ding, Yunchen Yang, Zhihui Zhu, Daniel P. Robinson, René Vidal, Laurent Kneip, Manolis C. Tsakiris:
Robust Homography Estimation via Dual Principal Component Pursuit. CVPR 2020: 6079-6088 - [c174]Ambar Pal, Connor Lane, René Vidal, Benjamin D. Haeffele:
On the Regularization Properties of Structured Dropout. CVPR 2020: 7668-7676 - [c173]Effrosyni Mavroudi, Benjamín Béjar Haro, René Vidal:
Representation Learning on Visual-Symbolic Graphs for Video Understanding. ECCV (29) 2020: 71-90 - [c172]Carolina Pacheco, Effrosyni Mavroudi, Elena Kokkoni, Herbert G. Tanner, René Vidal:
A Detection-based Approach to Multiview Action Classification in Infants. ICPR 2020: 6112-6119 - [c171]Guilherme França, Jeremias Sulam, Daniel P. Robinson, René Vidal:
Conformal Symplectic and Relativistic Optimization. NeurIPS 2020 - [c170]Paris Giampouras, René Vidal, Athanasios A. Rontogiannis, Benjamin D. Haeffele:
A novel variational form of the Schatten-$p$ quasi-norm. NeurIPS 2020 - [c169]Ambar Pal, René Vidal:
A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses. NeurIPS 2020 - [i57]Qing Qu, Zhihui Zhu, Xiao Li, Manolis C. Tsakiris, John Wright, René Vidal:
Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications. CoRR abs/2001.06970 (2020) - [i56]Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal:
Is an Affine Constraint Needed for Affine Subspace Clustering? CoRR abs/2005.03888 (2020) - [i55]Chong You, Chi Li, Daniel P. Robinson, René Vidal:
Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces. CoRR abs/2006.04246 (2020) - [i54]Ambar Pal, René Vidal:
A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses. CoRR abs/2009.06530 (2020) - [i53]Benjamin D. Haeffele, Chong You, René Vidal:
A Critique of Self-Expressive Deep Subspace Clustering. CoRR abs/2010.03697 (2020) - [i52]Paris Giampouras, René Vidal, Athanasios A. Rontogiannis, Benjamin D. Haeffele:
A novel variational form of the Schatten-p quasi-norm. CoRR abs/2010.13927 (2020) - [i51]Derek Lim, René Vidal, Benjamin D. Haeffele:
Doubly Stochastic Subspace Clustering. CoRR abs/2011.14859 (2020)
2010 – 2019
- 2019
- [j52]Evan Schwab, Benjamin D. Haeffele, René Vidal, Nicolas Charon:
Global Optimality in Separable Dictionary Learning with Applications to the Analysis of Diffusion MRI. SIAM J. Imaging Sci. 12(4): 1967-2008 (2019) - [c168]Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal:
Is an Affine Constraint Needed for Affine Subspace Clustering? ICCV 2019: 9914-9923 - [c167]Connor Lane, Ron Boger, Chong You, Manolis C. Tsakiris, Benjamin D. Haeffele, René Vidal:
Classifying and Comparing Approaches to Subspace Clustering with Missing Data. ICCV Workshops 2019: 669-677 - [c166]Connor Lane, Benjamin D. Haeffele, René Vidal:
Adaptive Online k-Subspaces with Cooperative Re-Initialization. ICCV Workshops 2019: 678-688 - [c165]Tianyu Ding, Zhihui Zhu, Tianjiao Ding, Yunchen Yang, Daniel P. Robinson, Manolis C. Tsakiris, René Vidal:
Noisy Dual Principal Component Pursuit. ICML 2019: 1617-1625 - [c164]Benjamin D. Haeffele, Christian Pick, Ziduo Lin, Evelien Mathieu, Stuart C. Ray, René Vidal:
An Optical Model of Whole Blood for Detecting Platelets in Lens-Free Images. SASHIMI@MICCAI 2019: 140-150 - [c163]Florence Yellin, Benjamín Béjar Haro, Benjamin D. Haeffele, Evelien Mathieu, Christian Pick, Stuart C. Ray, René Vidal:
Joint Holographic Detection and Reconstruction. MLMI@MICCAI 2019: 664-672 - [c162]Carolina Pacheco, René Vidal:
An Unsupervised Domain Adaptation Approach to Classification of Stem Cell-Derived Cardiomyocytes. MICCAI (1) 2019: 806-814 - [c161]Zhihui Zhu, Tianyu Ding, Daniel P. Robinson, Manolis C. Tsakiris, René Vidal:
A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning. NeurIPS 2019: 9437-9447 - [i50]Effrosyni Mavroudi, Benjamín Béjar Haro, René Vidal:
Neural Message Passing on Hybrid Spatio-Temporal Visual and Symbolic Graphs for Video Understanding. CoRR abs/1905.07385 (2019) - [i49]Guilherme França, Daniel P. Robinson, René Vidal:
Gradient Flows and Accelerated Proximal Splitting Methods. CoRR abs/1908.00865 (2019) - [i48]Benjamín Béjar Haro, Ivan Dokmanic, René Vidal:
The fastest 𝓁1, ∞ prox in the west. CoRR abs/1910.03749 (2019) - [i47]Mustafa Devrim Kaba, Mengnan Zhao, René Vidal, Daniel P. Robinson, Enrique Mallada:
Generalized Nullspace Property for Structurally Sparse Signals. CoRR abs/1910.05652 (2019) - [i46]Ambar Pal, Connor Lane, René Vidal, Benjamin D. Haeffele:
On the Regularization Properties of Structured Dropout. CoRR abs/1910.14186 (2019) - [i45]Daniel P. Robinson, René Vidal, Chong You:
Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis. CoRR abs/1912.13091 (2019) - 2018
- [j51]Hao Jiang, Daniel P. Robinson, René Vidal, Chong You:
A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis. Comput. Optim. Appl. 70(2): 395-418 (2018) - [j50]Manolis C. Tsakiris, René Vidal:
Dual Principal Component Pursuit. J. Mach. Learn. Res. 19: 18:1-18:50 (2018) - [j49]Thierry Bouwmans, Namrata Vaswani, Paul Rodríguez, René Vidal, Zhouchen Lin:
Introduction to the Issue on Robust Subspace Learning and Tracking: Theory, Algorithms, and Applications. IEEE J. Sel. Top. Signal Process. 12(6): 1127-1130 (2018) - [j48]Chun-Guang Li, Chong You, René Vidal:
On Geometric Analysis of Affine Sparse Subspace Clustering. IEEE J. Sel. Top. Signal Process. 12(6): 1520-1533 (2018) - [j47]Evan Schwab, René Vidal, Nicolas Charon:
Joint spatial-angular sparse coding for dMRI with separable dictionaries. Medical Image Anal. 48: 25-42 (2018) - [j46]Manolis C. Tsakiris, René Vidal:
Algebraic Clustering of Affine Subspaces. IEEE Trans. Pattern Anal. Mach. Intell. 40(2): 482-489 (2018) - [j45]Mihály Petreczky, René Vidal:
Realization Theory for a Class of Stochastic Bilinear Systems. IEEE Trans. Autom. Control. 63(1): 69-84 (2018) - [c160]Jacopo Cavazza, Pietro Morerio, Benjamin D. Haeffele, Connor Lane, Vittorio Murino, René Vidal:
Dropout as a Low-Rank Regularizer for Matrix Factorization. AISTATS 2018: 435-444 - [c159]Siddharth Mahendran, Haider Ali, René Vidal:
A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D Images. BMVC 2018: 72 - [c158]Mengnan Zhao, M. Devrim Kaba, René Vidal, Daniel P. Robinson, Enrique Mallada:
Sparse Recovery over Graph Incidence Matrices. CDC 2018: 364-371 - [c157]Florence Yellin, Benjamin D. Haeffele, Sophie Roth, René Vidal:
Multi-Cell Detection and Classification Using a Generative Convolutional Model. CVPR 2018: 8953-8961 - [c156]Chong You, Chi Li, Daniel P. Robinson, René Vidal:
A Scalable Exemplar-Based Subspace Clustering Algorithm for Class-Imbalanced Data. ECCV (9) 2018: 68-85 - [c155]Siddharth Mahendran, Haider Ali, René Vidal:
Convolutional Networks for Object Category and 3D Pose Estimation from 2D Images. ECCV Workshops (1) 2018: 698-715 - [c154]Guilherme França, Daniel P. Robinson, René Vidal:
ADMM and Accelerated ADMM as Continuous Dynamical Systems. ICML 2018: 1554-1562 - [c153]Poorya Mianjy, Raman Arora, René Vidal:
On the Implicit Bias of Dropout. ICML 2018: 3537-3545 - [c152]Manolis C. Tsakiris, René Vidal:
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries. ICML 2018: 4982-4991 - [c151]Carolina Pacheco, René Vidal:
Recurrent Neural Networks for Classifying Human Embryonic Stem Cell-Derived Cardiomyocytes. MICCAI (1) 2018: 581-589 - [c150]Zhihui Zhu, Yifan Wang, Daniel P. Robinson, Daniel Q. Naiman, René Vidal, Manolis C. Tsakiris:
Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms. NeurIPS 2018: 2175-2185 - [c149]Effrosyni Mavroudi, Divya Bhaskara, Shahin Sefati, Haider Ali, René Vidal:
End-to-End Fine-Grained Action Segmentation and Recognition Using Conditional Random Field Models and Discriminative Sparse Coding. WACV 2018: 1558-1567 - [i44]Manolis C. Tsakiris, René Vidal:
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries. CoRR abs/1801.00393 (2018) - [i43]Effrosyni Mavroudi, Divya Bhaskara, Shahin Sefati, Haider Ali, René Vidal:
End-to-End Fine-Grained Action Segmentation and Recognition Using Conditional Random Field Models and Discriminative Sparse Coding. CoRR abs/1801.09571 (2018) - [i42]Mengnan Zhao, M. Devrim Kaba, René Vidal, Daniel P. Robinson, Enrique Mallada:
Sparse Recovery over Graph Incidence Matrices: Polynomial Time Guarantees and Location Dependent Performance. CoRR abs/1803.09631 (2018) - [i41]Siddharth Mahendran, Haider Ali, René Vidal:
A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D Images. CoRR abs/1805.03225 (2018) - [i40]Poorya Mianjy, Raman Arora, René Vidal:
On the Implicit Bias of Dropout. CoRR abs/1806.09777 (2018) - [i39]Evan Schwab, Benjamin D. Haeffele, Nicolas Charon, René Vidal:
Separable Dictionary Learning with Global Optimality and Applications to Diffusion MRI. CoRR abs/1807.05595 (2018) - [i38]Siddharth Mahendran, Ming Yang Lu, Haider Ali, René Vidal:
Monocular Object Orientation Estimation using Riemannian Regression and Classification Networks. CoRR abs/1807.07226 (2018) - [i37]Chun-Guang Li, Chong You, René Vidal:
On Geometric Analysis of Affine Sparse Subspace Clustering. CoRR abs/1808.05965 (2018) - [i36]Xiao Li, Zhihui Zhu, Anthony Man-Cho So, René Vidal:
Nonconvex Robust Low-rank Matrix Recovery. CoRR abs/1809.09237 (2018) - [i35]Zhihui Zhu, Yifan Wang, Daniel P. Robinson, Daniel Q. Naiman, René Vidal, Manolis C. Tsakiris:
Dual Principal Component Pursuit: Probability Analysis and Efficient Algorithms. CoRR abs/1812.09924 (2018) - 2017
- [j44]Katsushi Ikeuchi, Christoph Schnörr, Josef Sivic, René Vidal:
Guest Editorial: Best Papers from ICCV 2015. Int. J. Comput. Vis. 125(1-3): 1-2 (2017) - [j43]Manolis C. Tsakiris, René Vidal:
Filtrated Algebraic Subspace Clustering. SIAM J. Imaging Sci. 10(1): 372-415 (2017) - [j42]Bijan Afsari, René Vidal:
Bundle Reduction and the Alignment Distance on Spaces of State-Space LTI Systems. IEEE Trans. Autom. Control. 62(8): 3804-3819 (2017) - [j41]Narges Ahmidi, Lingling Tao, Shahin Sefati, Yixin Gao, Colin Lea, Benjamín Béjar Haro, Luca Zappella, Sanjeev Khudanpur, René Vidal, Gregory D. Hager:
A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery. IEEE Trans. Biomed. Eng. 64(9): 2025-2041 (2017) - [j40]Chun-Guang Li, Chong You, René Vidal:
Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework. IEEE Trans. Image Process. 26(6): 2988-3001 (2017) - [c148]Siddharth Mahendran, Haider Ali, René Vidal:
3D Pose Regression Using Convolutional Neural Networks. CVPR Workshops 2017: 494-495 - [c147]Colin Lea, Michael D. Flynn, René Vidal, Austin Reiter, Gregory D. Hager:
Temporal Convolutional Networks for Action Segmentation and Detection. CVPR 2017: 1003-1012 - [c146]Chong You, Daniel P. Robinson, René Vidal:
Provable Self-Representation Based Outlier Detection in a Union of Subspaces. CVPR 2017: 4323-4332 - [c145]Benjamin D. Haeffele, René Vidal:
Global Optimality in Neural Network Training. CVPR 2017: 4390-4398 - [c144]Pietro Morerio, Jacopo Cavazza, Riccardo Volpi, René Vidal, Vittorio Murino:
Curriculum Dropout. ICCV 2017: 3564-3572 - [c143]Siddharth Mahendran, Haider Ali, René Vidal:
3D Pose Regression Using Convolutional Neural Networks. ICCV Workshops 2017: 2174-2182 - [c142]Wanxin Qu, Guoqing Zhou, Hao Zhu, Zhaolin Xiao, Qing Wang, René Vidal:
High angular resolution light field reconstruction with coded-aperture mask. ICIP 2017: 3036-3040 - [c141]Manolis C. Tsakiris, René Vidal:
Hyperplane Clustering via Dual Principal Component Pursuit. ICML 2017: 3472-3481 - [c140]Florence Yellin, Benjamin D. Haeffele, René Vidal:
Blood cell detection and counting in holographic lens-free imaging by convolutional sparse dictionary learning and coding. ISBI 2017: 650-653 - [c139]Benjamin D. Haeffele, Sophie Roth, Lin Zhou, René Vidal:
Removal of the twin image artifact in holographic lens-free imaging by sparse dictionary learning and coding. ISBI 2017: 741-744 - [c138]Benjamin D. Haeffele, Richard Stahl, Geert Vanmeerbeeck, René Vidal:
Efficient Reconstruction of Holographic Lens-Free Images by Sparse Phase Recovery. MICCAI (2) 2017: 109-117 - [c137]Effrosyni Mavroudi, Lingling Tao, René Vidal:
Deep Moving Poselets for Video Based Action Recognition. WACV 2017: 111-120 - [i34]Ehsan Jahangiri, Erdem Yörük, René Vidal, Laurent Younes, Donald Geman:
Information Pursuit: A Bayesian Framework for Sequential Scene Parsing. CoRR abs/1701.02343 (2017) - [i33]Pietro Morerio, Jacopo Cavazza, Riccardo Volpi, René Vidal, Vittorio Murino:
Curriculum Dropout. CoRR abs/1703.06229 (2017) - [i32]Chong You, Daniel P. Robinson, René Vidal:
Provable Self-Representation Based Outlier Detection in a Union of Subspaces. CoRR abs/1704.03925 (2017) - [i31]Manolis C. Tsakiris, René Vidal:
Hyperplane Clustering Via Dual Principal Component Pursuit. CoRR abs/1706.01604 (2017) - [i30]Evan Schwab, René Vidal, Nicolas Charon:
($k, q$)-Compressed Sensing for dMRI with Joint Spatial-Angular Sparsity Prior. CoRR abs/1707.09958 (2017) - [i29]Siddharth Mahendran, Haider Ali, René Vidal:
3D Pose Regression using Convolutional Neural Networks. CoRR abs/1708.05628 (2017) - [i28]Benjamin D. Haeffele, René Vidal:
Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications. CoRR abs/1708.07850 (2017) - [i27]Jacopo Cavazza, Connor Lane, Benjamin D. Haeffele, Vittorio Murino, René Vidal:
An Analysis of Dropout for Matrix Factorization. CoRR abs/1710.03487 (2017) - [i26]Jacopo Cavazza, Pietro Morerio, Benjamin D. Haeffele, Connor Lane, Vittorio Murino, René Vidal:
Dropout as a Low-Rank Regularizer for Matrix Factorization. CoRR abs/1710.05092 (2017) - [i25]Siddharth Mahendran, Haider Ali, René Vidal:
Joint Object Category and 3D Pose Estimation from 2D Images. CoRR abs/1711.07426 (2017) - [i24]Yunhan Zhao, Haider Ali, René Vidal:
Stretching Domain Adaptation: How far is too far? CoRR abs/1712.02286 (2017) - [i23]René Vidal, Joan Bruna, Raja Giryes, Stefano Soatto:
Mathematics of Deep Learning. CoRR abs/1712.04741 (2017) - [i22]Daniel Cremers, Laura Leal-Taixé, René Vidal:
Deep Learning for Computer Vision (Dagstuhl Seminar 17391). Dagstuhl Reports 7(9): 109-125 (2017) - 2016
- [b1]René Vidal, Yi Ma, S. Shankar Sastry:
Generalized Principal Component Analysis. Interdisciplinary applied mathematics 40, Springer 2016, ISBN 978-0-387-87810-2, pp. 1-566 - [j39]Ronen Basri, Cornelia Fermüller, Aleix M. Martínez, René Vidal:
Guest Editorial: Special Section on CVPR 2014. IEEE Trans. Pattern Anal. Mach. Intell. 38(7): 1281-1282 (2016) - [j38]Chun-Guang Li, René Vidal:
A Structured Sparse Plus Structured Low-Rank Framework for Subspace Clustering and Completion. IEEE Trans. Signal Process. 64(24): 6557-6570 (2016) - [c136]Chong You, Claire Donnat, Daniel P. Robinson, René Vidal:
A divide-and-conquer framework for large-scale subspace clustering. ACSSC 2016: 1014-1018 - [c135]Chong You, Daniel P. Robinson, René Vidal:
Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit. CVPR 2016: 3918-3927 - [c134]Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal:
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering. CVPR 2016: 3928-3937 - [c133]Colin Lea, Austin Reiter, René Vidal, Gregory D. Hager:
Segmental Spatiotemporal CNNs for Fine-Grained Action Segmentation. ECCV (3) 2016: 36-52 - [c132]