Cover Image

Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nguyen, Quan, Mehta, Nishant A., Guzmán, Cristóbal
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differentiable Distributionally Robust Optimization Layers
by: Ma, Xutao, et al.
Published: (2024)

Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis
by: Jiao, Yang, et al.
Published: (2023)

Nash Equilibria, Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization
by: Shafiee, Soroosh, et al.
Published: (2023)

Contextual Distributionally Robust Optimization with Causal and Continuous Structure: An Interpretable and Tractable Approach
by: Zhang, Fenglin, et al.
Published: (2026)

Distributionally Robust Safety Verification of Neural Networks via Worst-Case CVaR
by: Kishida, Masako
Published: (2025)

Near-Optimal Algorithms for Group Distributionally Robust Optimization and Beyond
by: Soma, Tasuku, et al.
Published: (2022)

Hindsight-Guided Momentum (HGM) Optimizer: An Approach to Adaptive Learning Rate
by: Sarkar, Krisanu
Published: (2025)

A Novel Unified Parametric Assumption for Nonconvex Optimization
by: Riabinin, Artem, et al.
Published: (2025)

The Ky Fan Norms and Beyond: Dual Norms and Combinations for Matrix Optimization
by: Kravatskiy, Alexey, et al.
Published: (2025)

DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty
by: Cui, Mingxuan, et al.
Published: (2025)

Deep Learning for Two-Stage Robust Integer Optimization
by: Dumouchelle, Justin, et al.
Published: (2023)

Adaptively Robust LLM Inference Optimization under Prediction Uncertainty
by: Chen, Zixi, et al.
Published: (2025)

Accelerated Rates between Stochastic and Adversarial Online Convex Optimization
by: Sachs, Sarah, et al.
Published: (2023)

Intersectional Fairness via Mixed-Integer Optimization
by: Němeček, Jiří, et al.
Published: (2026)

Parameter-Efficient Distributional RL via Normalizing Flows and a Geometry-Aware Cramér Surrogate
by: C., Simo Alami, et al.
Published: (2025)

$γ$-weakly $θ$-up-concavity: A Unified Framework for Non-Convex Optimization Beyond DR-Submodular and OSS Functions
by: Pedramfar, Mohammad, et al.
Published: (2026)

Online Submodular Maximization via Online Convex Optimization
by: Salem, Tareq Si, et al.
Published: (2023)

Unsupervised Machine Learning Hybrid Approach Integrating Linear Programming in Loss Function: A Robust Optimization Technique
by: Kiruluta, Andrew, et al.
Published: (2024)

Distributed Optimization via Energy Conservation Laws in Dilated Coordinates
by: Baranwal, Mayank, et al.
Published: (2024)

Memory-Efficient LLM Pretraining via Minimalist Optimizer Design
by: Glentis, Athanasios, et al.
Published: (2025)

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods
by: Hu, Hanyu, et al.
Published: (2025)

Hidden Convexity of Fair PCA and Fast Solver via Eigenvalue Optimization
by: Shen, Junhui, et al.
Published: (2025)

Uncovering Symmetry Transfer in Large Language Models via Layer-Peeled Optimization
by: Du, Zhehang, et al.
Published: (2026)

Policy Optimization in Hybrid Discrete-Continuous Action Spaces via Mixed Gradients
by: Alvo, Matias, et al.
Published: (2026)

Federated Majorize-Minimization: Beyond Parameter Aggregation
by: Dieuleveut, Aymeric, et al.
Published: (2025)

Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling
by: Meterez, Alexandru, et al.
Published: (2025)

Anytime Pretraining: Horizon-Free Learning-Rate Schedules with Weight Averaging
by: Meterez, Alexandru, et al.
Published: (2026)

Beyond Expectations: Learning with Stochastic Dominance Made Practical
by: Cen, Shicong, et al.
Published: (2024)

The Road Less Scheduled
by: Defazio, Aaron, et al.
Published: (2024)

Learning Concave Bid Shading Strategies in Online Auctions via Measure-valued Proximal Optimization
by: Nodozi, Iman, et al.
Published: (2025)

Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
by: Mehta, Ronak, et al.
Published: (2024)

Data Uniformity Improves Training Efficiency and More, with a Convergence Framework Beyond the NTK Regime
by: Wang, Yuqing, et al.
Published: (2025)

Robust Control with Gradient Uncertainty
by: Qi, Qian
Published: (2025)

Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency
by: Kan, Kelvin, et al.
Published: (2025)

Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent
by: Jing, Gangshan, et al.
Published: (2021)

Effective Bilevel Optimization via Minimax Reformulation
by: Wang, Xiaoyu, et al.
Published: (2023)

Delightful Distributed Policy Gradient
by: Osband, Ian
Published: (2026)

Dion: Distributed Orthonormalized Updates
by: Ahn, Kwangjun, et al.
Published: (2025)

Joint Problems in Learning Multiple Dynamical Systems
by: Niu, Mengjia, et al.
Published: (2023)

Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
by: Tran-Dinh, Quoc, et al.
Published: (2024)