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René Vidal

86 papers · 2006–2026 · 12 venues · across top CS/AI venues

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+15 more ↓ 🗺️ 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)

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