:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	He, Roy Y., Liu, Haixia, Liu, Hao
Format:	Preprint
Published:	2024
Subjects:	Information Theory Optimization and Control Machine Learning
Online Access:	https://arxiv.org/abs/2407.07707
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the Convergence Analysis of Muon
by: Shen, Wei, et al.
Published: (2025)

Finite-Time Minimax Bounds and an Optimal Lyapunov Policy in Queueing Control
by: Liu, Yujie, et al.
Published: (2025)

Convergence of linear programming hierarchies for Gibbs states of spin systems
by: Fawzi, Hamza, et al.
Published: (2025)

Accelerating Convergence of Score-Based Diffusion Models, Provably
by: Li, Gen, et al.
Published: (2024)

The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysis
by: Zurek, Matthew, et al.
Published: (2024)

Wasserstein Distributionally Robust Estimation in High Dimensions: Performance Analysis and Optimal Hyperparameter Tuning
by: Aolaritei, Liviu, et al.
Published: (2022)

Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD
by: Wang, Jiayi, et al.
Published: (2020)

Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
by: Li, Gen, et al.
Published: (2021)

Subspace Optimization for Large Language Models with Convergence Guarantees
by: He, Yutong, et al.
Published: (2024)

Linear Convergence in Hilbert's Projective Metric for Computing Augustin Information and a Rényi Information Measure
by: Tsai, Chung-En, et al.
Published: (2024)

ODELoRA: Training Low-Rank Adaptation by Solving Ordinary Differential Equations
by: Gao, Yihang, et al.
Published: (2026)

Automatic Rank Determination for Low-Rank Adaptation via Submodular Function Maximization
by: Gao, Yihang, et al.
Published: (2025)

On the Robustness of Cross-Concentrated Sampling for Matrix Completion
by: Cai, HanQin, et al.
Published: (2024)

Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
by: Zurek, Matthew, et al.
Published: (2024)

Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
by: Yu, Qian, et al.
Published: (2024)

Variational Inference on the Boolean Hypercube with the Quantum Entropy
by: Beyler, Eliot, et al.
Published: (2024)

Structured Sampling for Robust Euclidean Distance Geometry
by: Kundu, Chandra, et al.
Published: (2024)

Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation
by: Cui, Chengyu, et al.
Published: (2026)

Linear regression with overparameterized linear neural networks: Tight upper and lower bounds for implicit $\ell^1$-regularization
by: Matt, Hannes, et al.
Published: (2025)

Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares
by: Kümmerle, Christian, et al.
Published: (2023)

Generalized Orthogonal Procrustes Problem under Arbitrary Adversaries
by: Ling, Shuyang
Published: (2021)

Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs
by: Zamir, Guy, et al.
Published: (2026)

A Neural Network Algorithm for KL Divergence Estimation with Quantitative Error Bounds
by: Foss, Mikil, et al.
Published: (2025)

Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
by: Shen, Wei, et al.
Published: (2023)

Tight Regret Bounds for Bayesian Optimization in One Dimension
by: Scarlett, Jonathan
Published: (2018)

Span-Based Optimal Sample Complexity for Average Reward MDPs
by: Zurek, Matthew, et al.
Published: (2023)

A Dual Basis Approach for Structured Robust Euclidean Distance Geometry
by: Kundu, Chandra, et al.
Published: (2025)

The augmented NLP bound for maximum-entropy remote sampling
by: Ponte, Gabriel, et al.
Published: (2026)

A Single-Loop First-Order Algorithm for Linearly Constrained Bilevel Optimization
by: Shen, Wei, et al.
Published: (2025)

Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward RL
by: Zurek, Matthew, et al.
Published: (2025)

More is Less: Inducing Sparsity via Overparameterization
by: Chou, Hung-Hsu, et al.
Published: (2021)

Adversarial Water-Filling: Theory, Algorithms and Foundation Model
by: Tong, Xindi, et al.
Published: (2026)

Geometry, Computation, and Optimality in Stochastic Optimization
by: Cheng, Chen, et al.
Published: (2019)

Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL
by: Zurek, Matthew, et al.
Published: (2025)

MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation
by: Shen, Wei, et al.
Published: (2025)

Capabilities and Fundamental Limits of Latent Chain-of-Thought
by: Zou, Jiaxuan, et al.
Published: (2026)

Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces
by: Duan, Yaqi, et al.
Published: (2024)

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

The Local Landscape of Phase Retrieval Under Limited Samples
by: Liu, Kaizhao, et al.
Published: (2023)

Long-time dynamics and universality of nonconvex gradient descent
by: Han, Qiyang
Published: (2025)