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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
- 2023
[j62]Aditya Chattopadhyay
, Stewart Slocum, Benjamin D. Haeffele, René Vidal, Donald Geman:
Interpretable by Design: Learning Predictors by Composing Interpretable Queries. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7430-7443 (2023)- [j61]Guilherme França, Daniel P. Robinson, René Vidal:
A Nonsmooth Dynamical Systems Perspective on Accelerated Extensions of ADMM. IEEE Trans. Autom. Control. 68(5): 2966-2978 (2023) - [j60]Gregory N. McKay, Anisha Oommen, Carolina Pacheco, Mason T. Chen, Stuart C. Ray, René Vidal, Benjamin D. Haeffele, Nicholas J. Durr:
Lens Free Holographic Imaging for Urinary Tract Infection Screening. IEEE Trans. Biomed. Eng. 70(3): 1053-1061 (2023) - [c203]Ziqing Xu, Hancheng Min, Salma Tarmoun, Enrique Mallada, René Vidal:
Linear Convergence of Gradient Descent For Finite Width Over-parametrized Linear Networks With General Initialization. AISTATS 2023: 2262-2284 - [c202]Liangzu Peng, Christian Kümmerle, René Vidal:
On the Convergence of IRLS and Its Variants in Outlier-Robust Estimation. CVPR 2023: 17808-17818 - [c201]Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin David Haeffele, Donald Geman, René Vidal:
Variational Information Pursuit for Interpretable Predictions. ICLR 2023 - [c200]Juan Cerviño, Luiz F. O. Chamon, Benjamin David Haeffele, René Vidal, Alejandro Ribeiro:
Learning Globally Smooth Functions on Manifolds. ICML 2023: 3815-3854 - [c199]Hancheng Min, René Vidal, Enrique Mallada:
On the Convergence of Gradient Flow on Multi-layer Linear Models. ICML 2023: 24850-24887 - [c198]Liangzu Peng, Paris Giampouras, René Vidal:
The Ideal Continual Learner: An Agent That Never Forgets. ICML 2023: 27585-27610 - [c197]Aditya Chattopadhyay, Xi Zhang, David Paul Wipf, Himanshu Arora, René Vidal:
Learning Graph Variational Autoencoders with Constraints and Structured Priors for Conditional Indoor 3D Scene Generation. WACV 2023: 785-794 - [i81]Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin D. Haeffele, Donald Geman, René Vidal:
Variational Information Pursuit for Interpretable Predictions. CoRR abs/2302.02876 (2023) - [i80]Kyle Poe, Enrique Mallada, René Vidal:
Necessary and Sufficient Conditions for Simultaneous State and Input Recovery of Linear Systems with Sparse Inputs by 𝓁1-Minimization. CoRR abs/2304.05526 (2023) - [i79]Liangzu Peng, Paris V. Giampouras, René Vidal:
The Ideal Continual Learner: An Agent That Never Forgets. CoRR abs/2305.00316 (2023) - [i78]Kaleab Alemayehu Kinfu, René Vidal:
Efficient Vision Transformer for Human Pose Estimation via Patch Selection. CoRR abs/2306.04225 (2023) - [i77]Darshan Thaker, Paris Giampouras, René Vidal:
A Linearly Convergent GAN Inversion-based Algorithm for Reverse Engineering of Deceptions. CoRR abs/2306.04756 (2023) - [i76]Tianzhe Chu, Shengbang Tong, Tianjiao Ding, Xili Dai, Benjamin David Haeffele, René Vidal, Yi Ma:
Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models. CoRR abs/2306.05272 (2023) - [i75]Hancheng Min, René Vidal, Enrique Mallada:
Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization. CoRR abs/2307.12851 (2023) - [i74]Kwan Ho Ryan Chan, Aditya Chattopadhyay, Benjamin David Haeffele, René Vidal:
Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions. CoRR abs/2308.12562 (2023) - 2022
- [j59]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) - [j58]Benjamín Béjar Haro, Ivan Dokmanic, René Vidal:
The Fastest $\ell _{1, \infty }$ℓ1, ∞ Prox in the West. IEEE Trans. Pattern Anal. Mach. Intell. 44(7): 3858-3869 (2022) - [c196]Kaleab Alemayehu Kinfu, René Vidal:
Analysis and Extensions of Adversarial Training for Video Classification. CVPR Workshops 2022: 3415-3424 - [c195]Liangzu Peng, Manolis C. Tsakiris, René Vidal:
ARCS: Accurate Rotation and Correspondence Search. CVPR 2022: 11143-11153 - [c194]Effrosyni Mavroudi, René Vidal:
Weakly-Supervised Generation and Grounding of Visual Descriptions with Conditional Generative Models. CVPR 2022: 15523-15533 - [c193]Liangzu Peng, Mahyar Fazlyab, René Vidal:
Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search: Tight or Not. ECCV (23) 2022: 673-691 - [c192]Paris Giampouras, Benjamin David Haeffele, René Vidal:
Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension. ICLR 2022 - [c191]Tianjiao Ding, Derek Lim, René Vidal, Benjamin D. Haeffele:
Understanding Doubly Stochastic Clustering. ICML 2022: 5153-5165 - [c190]Darshan Thaker, Paris Giampouras, René Vidal:
Reverse Engineering ℓp attacks: A block-sparse optimization approach with recovery guarantees. ICML 2022: 21253-21271 - [c189]Yutao Tang, Benjamín Béjar, Joey K.-Y. Essoe, Joseph F. McGuire, René Vidal:
Facial Tic Detection in Untrimmed Videos of Tourette Syndrome Patients. ICPR 2022: 3152-3159 - [c188]René Vidal:
Semantic Information Pursuit. IMPROVE 2022: 9 - [c187]Liangzu Peng, Christian Kümmerle, René Vidal:
Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression. NeurIPS 2022 - [c186]Effrosyni Mavroudi, Prashast Bindal, René Vidal:
Actor-Centric Tubelets for Real-Time Activity Detection in Extended Videos. WACV (Workshops) 2022: 172-181 - [i73]Joshua T. Vogelstein, Timothy D. 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 H. 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) - [i72]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) - [i71]Darshan Thaker, Paris Giampouras, René Vidal:
Reverse Engineering 𝓁p attacks: A block-sparse optimization approach with recovery guarantees. CoRR abs/2203.04886 (2022) - [i70]Liangzu Peng, Manolis C. Tsakiris, René Vidal:
ARCS: Accurate Rotation and Correspondence Search. CoRR abs/2203.14493 (2022) - [i69]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) - [i68]Danny Weyns, Thomas Bäck, René Vidal, Xin Yao, Ahmed Nabil Belbachir:
The Vision of Self-Evolving Computing Systems. CoRR abs/2204.06825 (2022) - [i67]Kaleab Alemayehu Kinfu, René Vidal:
Analysis and Extensions of Adversarial Training for Video Classification. CoRR abs/2206.07953 (2022) - [i66]Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele, René Vidal, Donald Geman:
Interpretable by Design: Learning Predictors by Composing Interpretable Queries. CoRR abs/2207.00938 (2022) - [i65]Liangzu Peng, Mahyar Fazlyab, René Vidal:
Towards Understanding The Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search. CoRR abs/2207.08350 (2022) - [i64]Juan Cerviño, Luiz F. O. Chamon, Benjamin D. Haeffele, René Vidal, Alejandro Ribeiro:
Learning Globally Smooth Functions on Manifolds. CoRR abs/2210.00301 (2022) - [i63]Yutao Tang, Benjamín Béjar, Joey K.-Y. Essoe, Joseph F. McGuire, René Vidal:
Facial Tic Detection in Untrimmed Videos of Tourette Syndrome Patients. CoRR abs/2211.03895 (2022) - [i62]Ambar Pal, Arnau Ramisa, Amit Kumar K. C, René Vidal:
On Utilizing Relationships for Transferable Few-Shot Fine-Grained Object Detection. CoRR abs/2212.00770 (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) - [c185]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 - [c184]Shangzhi Zhang, Chong You, René Vidal, Chun-Guang Li:
Learning a Self-Expressive Network for Subspace Clustering. CVPR 2021: 12393-12403 - [c183]Benjamin David Haeffele, Chong You, René Vidal:
A Critique of Self-Expressive Deep Subspace Clustering. ICLR 2021 - [c182]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 - [c181]Mustafa Devrim Kaba, Chong You, Daniel P. Robinson, Enrique Mallada, René Vidal:
A Nullspace Property for Subspace-Preserving Recovery. ICML 2021: 5180-5188 - [c180]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 - [c179]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) - [c178]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 - [c177]Ambar Pal, Connor Lane, René Vidal, Benjamin D. Haeffele:
On the Regularization Properties of Structured Dropout. CVPR 2020: 7668-7676 - [c176]Effrosyni Mavroudi, Benjamín Béjar Haro, René Vidal:
Representation Learning on Visual-Symbolic Graphs for Video Understanding. ECCV (29) 2020: 71-90 - [c175]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 - [c174]Guilherme França, Jeremias Sulam, Daniel P. Robinson, René Vidal:
Conformal Symplectic and Relativistic Optimization. NeurIPS 2020 - [c173]Paris Giampouras, René Vidal, Athanasios A. Rontogiannis, Benjamin D. Haeffele:
A novel variational form of the Schatten-$p$ quasi-norm. NeurIPS 2020 - [c172]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) - [c171]Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal:
Is an Affine Constraint Needed for Affine Subspace Clustering? ICCV 2019: 9914-9923 - [c170]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 - [c169]Connor Lane, Benjamin D. Haeffele, René Vidal:
Adaptive Online k-Subspaces with Cooperative Re-Initialization. ICCV Workshops 2019: 678-688 - [c168]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 - [c167]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 - [c166]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 - [c165]Carolina Pacheco, René Vidal:
An Unsupervised Domain Adaptation Approach to Classification of Stem Cell-Derived Cardiomyocytes. MICCAI (1) 2019: 806-814 - [c164]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) - [c163]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 - [c162]Siddharth Mahendran, Haider Ali, René Vidal:
A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D Images. BMVC 2018: 72 - [c161]Mengnan Zhao, M. Devrim Kaba, René Vidal, Daniel P. Robinson, Enrique Mallada:
Sparse Recovery over Graph Incidence Matrices. CDC 2018: 364-371 - [c160]Florence Yellin, Benjamin D. Haeffele, Sophie Roth, René Vidal:
Multi-Cell Detection and Classification Using a Generative Convolutional Model. CVPR 2018: 8953-8961 - [c159]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 - [c158]Siddharth Mahendran, Haider Ali, René Vidal:
Convolutional Networks for Object Category and 3D Pose Estimation from 2D Images. ECCV Workshops (1) 2018: 698-715 - [c157]Guilherme França, Daniel P. Robinson, René Vidal:
ADMM and Accelerated ADMM as Continuous Dynamical Systems. ICML 2018: 1554-1562 - [c156]Poorya Mianjy, Raman Arora, René Vidal:
On the Implicit Bias of Dropout. ICML 2018: 3537-3545 - [c155]Manolis C. Tsakiris, René Vidal:
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries. ICML 2018: 4982-4991 - [c154]Carolina Pacheco, René Vidal:
Recurrent Neural Networks for Classifying Human Embryonic Stem Cell-Derived Cardiomyocytes. MICCAI (1) 2018: 581-589 - [c153]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 - [c152]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) - [c151]