Cover Image

Straight-Through meets Sparse Recovery: the Support Exploration Algorithm

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mohamed, Mimoun, Malgouyres, François, Emiya, Valentin, Chaux, Caroline
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Optimization and Control Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Geometry-induced Regularization in Deep ReLU Neural Networks
by: Bona-Pellissier, Joachim, et al.
Published: (2024)

FraPPE: Fast and Efficient Preference-based Pure Exploration
by: Das, Udvas, et al.
Published: (2025)

Statistical and Algorithmic Foundations of Reinforcement Learning
by: Chi, Yuejie, et al.
Published: (2025)

Smooth Non-Stationary Bandits
by: Jia, Su, et al.
Published: (2023)

Piecewise Polynomial Regression of Tame Functions via Integer Programming
by: Bareilles, Gilles, et al.
Published: (2023)

Decoupled Continuous-Time Reinforcement Learning via Hamiltonian Flow
by: Nguyen, Minh
Published: (2026)

Byzantine Machine Learning: MultiKrum and an optimal notion of robustness
by: Bareilles, Gilles, et al.
Published: (2026)

Sinkhorn Based Associative Memory Retrieval Using Spherical Hellinger Kantorovich Dynamics
by: Mustafi, Aratrika, et al.
Published: (2026)

Inverse Mixed-Integer Programming: Learning Constraints then Objective Functions
by: Kitaoka, Akira
Published: (2025)

A Differential and Pointwise Control Approach to Reinforcement Learning
by: Nguyen, Minh, et al.
Published: (2024)

Precise gradient descent training dynamics for finite-width multi-layer neural networks
by: Han, Qiyang, et al.
Published: (2025)

Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality
by: Chen, Siyu, et al.
Published: (2024)

Learning to Fuse Temporal Proximity Networks: A Case Study in Chimpanzee Social Interactions
by: He, Yixuan, et al.
Published: (2025)

Sail into the Headwind: Alignment via Robust Rewards and Dynamic Labels against Reward Hacking
by: Rashidinejad, Paria, et al.
Published: (2024)

Optimism Stabilizes Thompson Sampling for Adaptive Inference
by: Yan, Shunxing, et al.
Published: (2026)

Sparse PCA With Multiple Components
by: Cory-Wright, Ryan, et al.
Published: (2022)

Decentralized Sparse Linear Regression via Gradient-Tracking: Linear Convergence and Statistical Guarantees
by: Maros, Marie, et al.
Published: (2022)

Variational Transport: A Convergent Particle-BasedAlgorithm for Distributional Optimization
by: Yang, Zhuoran, et al.
Published: (2020)

Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space
by: Jiang, Yiheng, et al.
Published: (2023)

An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling
by: Huang, Xunpeng, et al.
Published: (2024)

Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity
by: Bravo, Mario, et al.
Published: (2025)

The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
by: Collins-Woodfin, Elizabeth, et al.
Published: (2024)

Quantized Approximately Orthogonal Recurrent Neural Networks
by: Foucault, Armand, et al.
Published: (2024)

Analytic Bridge Diffusions for Controlled Path Generation
by: Chertkov, Michael
Published: (2026)

A Graphical Global Optimization Framework for Parameter Estimation of Statistical Models with Nonconvex Regularization Functions
by: Davarnia, Danial, et al.
Published: (2025)

Piecewise Linearity of Min-Norm Solution Map of a Nonconvexly Regularized Convex Sparse Model
by: Zhang, Yi, et al.
Published: (2023)

Delightful Exploration
by: Osband, Ian
Published: (2026)

Inference with the Upper Confidence Bound Algorithm
by: Khamaru, Koulik, et al.
Published: (2024)

Progressive Feedforward Collapse of ResNet Training
by: Wang, Sicong, et al.
Published: (2024)

A Theory of Feature Learning in Kernel Models
by: Chen, Yunlu, et al.
Published: (2023)

Convergence of flow-based generative models via proximal gradient descent in Wasserstein space
by: Cheng, Xiuyuan, et al.
Published: (2023)

A New Perspective On Denoising Based On Optimal Transport
by: Trillos, Nicolas Garcia, et al.
Published: (2023)

Certified Multi-Fidelity Zeroth-Order Optimization
by: de Montbrun, Étienne, et al.
Published: (2023)

High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise
by: Armacki, Aleksandar, et al.
Published: (2023)

Learning the Uncertainty Sets for Control Dynamics via Set Membership: A Non-Asymptotic Analysis
by: Li, Yingying, et al.
Published: (2023)

Bayesian Design Principles for Frequentist Sequential Learning
by: Xu, Yunbei, et al.
Published: (2023)

A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
by: Alfano, Carlo, et al.
Published: (2023)

Stochastic Optimization with Optimal Importance Sampling
by: Aolaritei, Liviu, et al.
Published: (2025)

Joint learning of a network of linear dynamical systems via total variation penalization
by: Donnat, Claire, et al.
Published: (2025)

A review of NMF, PLSA, LBA, EMA, and LCA with a focus on the identifiability issue
by: Qi, Qianqian, et al.
Published: (2025)