René Vidal
86 papers · 2006–2026 · 12 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (105) 🌍 Conference Polyglot · Gold 🏃 Academic Marathon · Ultra 🌉 Interdisciplinary Bridge · Gold 🐣 Hot Topic Early Bird
🏠
Conference Loyalist
(21)
🌱
Topic Pioneer
🔬
Deep Specialist
(19)
👑
Triple Crown
🏆
Keyword Champion
(9)
🧭
Keyword Pioneer
🌟
Keyword Trendsetter Combo
(6)
🌈
Renaissance Researcher
(7)
🔥
Unstoppable · Gold
❓
The Questioner
(2)
⚡
Prolific Year · Prolific
🚀
Conference Pioneer
💎
Century Club · Silver
📈
Trend Setter
🗃️
Keyword Collector
(359)
Venues
Top co-authors
Research topics
Machine Learning
(65)
Core Methods
(37)
Optimization & Theory · Machine Learning
(36)
Mathematics & Optimization
(33)
Optimization
(30)
Deep Learning
(27)
Learning Types
(24)
Computer Vision
(19)
Artificial Intelligence
(14)
Core AI
(14)
Analysis
(12)
Mathematics
(12)
Models
(10)
Optimization & Theory · Deep Learning
(7)
Architectures
(6)
Keywords
subspace clustering
(9)
non-convex optimization
(8)
outlier detection
(6)
subspace learning
(6)
dual principal component pursuit
(6)
sparse coding
(6)
matrix factorization
(5)
gradient flow
(5)
spectral clustering
(5)
dimensionality reduction
(4)
neural network
(4)
sparse representation
(4)
image classification
(4)
convex optimization
(4)
adversarial robustness
(4)
representation learning
(4)
implicit bia
(4)
gradient descent
(3)
dictionary learning
(3)
sparse recovery
(3)
Papers
Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs
CVPR 2026
Hierarchical Concept Embedding & Pursuit for Interpretable Image Classification
CVPR 2026
ImageRAGTurbo: Towards One-step Text-to-Image Generation with Retrieval-Augmented Diffusion Models
CVPR 2026
A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks
AISTATS 2025
Concept Lancet: Image Editing with Compositional Representation Transplant
CVPR 2025
Disentangling Safe and Unsafe Image Corruptions via Anisotropy and Locality
CVPR 2025
Frequency-Guided Posterior Sampling for Diffusion-Based Image Restoration
ICCV 2025
Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs
ICML 2025
Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
ICML 2025
InCoDe: Interpretable Compressed Descriptions For Image Generation
ICLR 2025
IP-CRR: Information Pursuit for Interpretable Classification of Chest Radiology Reports
MICCAI 2025
Learning Interpretable Queries for Explainable Image Classification with Information Pursuit
ICCV 2025
LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning
ICLR 2025
Nonconvex Linear System Identification with Minimal State Representation
L4DC 2025
Understanding the Learning Dynamics of LoRA: A Gradient Flow Perspective on Low-Rank Adaptation in Matrix Factorization
AISTATS 2025
Voyaging into Perpetual Dynamic Scenes from a Single View
ICCV 2025
Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification
ICLR 2024
Can Implicit Bias Imply Adversarial Robustness?
ICML 2024
Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization
ICLR 2024
Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representation
ACL 2024
Geometric Analysis of Nonlinear Manifold Clustering
NeurIPS 2024
iHealth-Chile-3&2 at RRG24: Template Based Report Generation
ACL 2024
Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models
ICLR 2024
PaCE: Parsimonious Concept Engineering for Large Language Models
NeurIPS 2024
Performance Bounds for Active Binary Testing with Information Maximization
ICML 2024
Scalable 3D Registration via Truncated Entry-wise Absolute Residuals
CVPR 2024
Semantic-Aware Video Representation for Few-Shot Action Recognition
WACV 2024
Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalities
AISTATS 2024
Vertex Proportion Loss for Multi-Class Cell Detection from Label Proportions
MICCAI 2024
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness
NeurIPS 2023
Information Maximization Perspective of Orthogonal Matching Pursuit with Applications to Explainable AI
NeurIPS 2023
Learning Globally Smooth Functions on Manifolds
ICML 2023
Learning Graph Variational Autoencoders With Constraints and Structured Priors for Conditional Indoor 3D Scene Generation
WACV 2023
Linear Convergence of Gradient Descent For Finite Width Over-parametrized Linear Networks With General Initialization
AISTATS 2023
On the Convergence of Gradient Flow on Multi-layer Linear Models
ICML 2023
On the Convergence of IRLS and Its Variants in Outlier-Robust Estimation
CVPR 2023
The Ideal Continual Learner: An Agent That Never Forgets
ICML 2023
Variational Information Pursuit for Interpretable Predictions
ICLR 2023
ARCS: Accurate Rotation and Correspondence Search
CVPR 2022
Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression
NeurIPS 2022
Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension
ICLR 2022
Reverse Engineering ℓ_p attacks: A block-sparse optimization approach with recovery guarantees
ICML 2022
Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search: Tight or Not
ECCV 2022
Understanding Doubly Stochastic Clustering
ICML 2022
Weakly-Supervised Generation and Grounding of Visual Descriptions With Conditional Generative Models
CVPR 2022
A Critique of Self-Expressive Deep Subspace Clustering
ICLR 2021
A Nullspace Property for Subspace-Preserving Recovery
ICML 2021
Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms
AISTATS 2021
Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach
ICML 2021
Learning a Self-Expressive Network for Subspace Clustering
CVPR 2021
On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
ICML 2021
Understanding the Dynamics of Gradient Flow in Overparameterized Linear models
ICML 2021
A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses
NeurIPS 2020
A novel variational form of the Schatten-p quasi-norm
NeurIPS 2020
Conformal Symplectic and Relativistic Optimization
NeurIPS 2020
On the Regularization Properties of Structured Dropout
CVPR 2020
Representation Learning on Visual-Symbolic Graphs for Video Understanding
ECCV 2020
Robust Homography Estimation via Dual Principal Component Pursuit
CVPR 2020
A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning
NeurIPS 2019
Is an Affine Constraint Needed for Affine Subspace Clustering?
ICCV 2019
Noisy Dual Principal Component Pursuit
ICML 2019
ADMM and Accelerated ADMM as Continuous Dynamical Systems
ICML 2018
Dropout as a Low-Rank Regularizer for Matrix Factorization
AISTATS 2018
Dual Principal Component Pursuit
JMLR 2018
Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms
NeurIPS 2018
Multi-Cell Detection and Classification Using a Generative Convolutional Model
CVPR 2018
On the Implicit Bias of Dropout
ICML 2018
Scalable Exemplar-based Subspace Clustering on Class-Imbalanced Data
ECCV 2018
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
ICML 2018
Curriculum Dropout
ICCV 2017
Global Optimality in Neural Network Training
CVPR 2017
Hyperplane Clustering via Dual Principal Component Pursuit
ICML 2017
Provable Self-Representation Based Outlier Detection in a Union of Subspaces
CVPR 2017
Temporal Convolutional Networks for Action Segmentation and Detection
CVPR 2017
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering
CVPR 2016
Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit
CVPR 2016
Geometric Conditions for Subspace-Sparse Recovery
ICML 2015
Sparse Subspace Clustering with Missing Entries
ICML 2015
Structured Sparse Subspace Clustering: A Unified Optimization Framework
CVPR 2015
Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing
ICML 2014
Coarse-to-Fine Semantic Video Segmentation Using Supervoxel Trees
ICCV 2013
Hierarchical Joint Max-Margin Learning of Mid and Top Level Representations for Visual Recognition
ICCV 2013
Latent Space Sparse Subspace Clustering
ICCV 2013
Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery
NeurIPS 2012
Sparse Manifold Clustering and Embedding
NeurIPS 2011
Online Clustering of Moving Hyperplanes
NeurIPS 2006