Adversarial Water-Filling: Theory, Algorithms and Foundation Model
Fuente:
arXiv
Saved in:
| Main Authors: | Tong, Xindi, Tan, Chee Wei, Poor, H. Vincent |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning to Optimize by Differentiable Programming
by: Tao, Liping, et al.
Published: (2026)
by: Tao, Liping, et al.
Published: (2026)
Finite-Time Minimax Bounds and an Optimal Lyapunov Policy in Queueing Control
by: Liu, Yujie, et al.
Published: (2025)
by: Liu, Yujie, et al.
Published: (2025)
Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods
by: Li, Gen, et al.
Published: (2023)
by: Li, Gen, et al.
Published: (2023)
A Single-Loop First-Order Algorithm for Linearly Constrained Bilevel Optimization
by: Shen, Wei, et al.
Published: (2025)
by: Shen, Wei, et al.
Published: (2025)
Generalized Orthogonal Procrustes Problem under Arbitrary Adversaries
by: Ling, Shuyang
Published: (2021)
by: Ling, Shuyang
Published: (2021)
ODELoRA: Training Low-Rank Adaptation by Solving Ordinary Differential Equations
by: Gao, Yihang, et al.
Published: (2026)
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)
by: Gao, Yihang, et al.
Published: (2025)
A Neural Network Algorithm for KL Divergence Estimation with Quantitative Error Bounds
by: Foss, Mikil, et al.
Published: (2025)
by: Foss, Mikil, et al.
Published: (2025)
MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation
by: Shen, Wei, et al.
Published: (2025)
by: Shen, Wei, et al.
Published: (2025)
Parameter-free Algorithms for the Stochastically Extended Adversarial Model
by: Wang, Shuche, et al.
Published: (2025)
by: Wang, Shuche, et al.
Published: (2025)
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
by: Li, Gen, et al.
Published: (2020)
by: Li, Gen, et al.
Published: (2020)
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
by: Shen, Wei, et al.
Published: (2023)
by: Shen, Wei, et al.
Published: (2023)
On the Convergence Analysis of Muon
by: Shen, Wei, et al.
Published: (2025)
by: Shen, Wei, et al.
Published: (2025)
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
by: Li, Gen, et al.
Published: (2021)
by: Li, Gen, et al.
Published: (2021)
Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation
by: Cui, Chengyu, et al.
Published: (2026)
by: Cui, Chengyu, et al.
Published: (2026)
Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs
by: Zamir, Guy, et al.
Published: (2026)
by: Zamir, Guy, et al.
Published: (2026)
The augmented NLP bound for maximum-entropy remote sampling
by: Ponte, Gabriel, et al.
Published: (2026)
by: Ponte, Gabriel, et al.
Published: (2026)
High-probability sample complexities for policy evaluation with linear function approximation
by: Li, Gen, et al.
Published: (2023)
by: Li, Gen, et al.
Published: (2023)
Linear regression with overparameterized linear neural networks: Tight upper and lower bounds for implicit $\ell^1$-regularization
by: Matt, Hannes, et al.
Published: (2025)
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)
by: Kümmerle, Christian, et al.
Published: (2023)
On the Robustness of Cross-Concentrated Sampling for Matrix Completion
by: Cai, HanQin, et al.
Published: (2024)
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)
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)
by: Yu, Qian, et al.
Published: (2024)
Tight Regret Bounds for Bayesian Optimization in One Dimension
by: Scarlett, Jonathan
Published: (2018)
by: Scarlett, Jonathan
Published: (2018)
The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysis
by: Zurek, Matthew, et al.
Published: (2024)
by: Zurek, Matthew, et al.
Published: (2024)
Variational Inference on the Boolean Hypercube with the Quantum Entropy
by: Beyler, Eliot, et al.
Published: (2024)
by: Beyler, Eliot, et al.
Published: (2024)
Span-Based Optimal Sample Complexity for Average Reward MDPs
by: Zurek, Matthew, et al.
Published: (2023)
by: Zurek, Matthew, et al.
Published: (2023)
A Dual Basis Approach for Structured Robust Euclidean Distance Geometry
by: Kundu, Chandra, et al.
Published: (2025)
by: Kundu, Chandra, et al.
Published: (2025)
Structured Sampling for Robust Euclidean Distance Geometry
by: Kundu, Chandra, et al.
Published: (2024)
by: Kundu, Chandra, et al.
Published: (2024)
Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward RL
by: Zurek, Matthew, et al.
Published: (2025)
by: Zurek, Matthew, et al.
Published: (2025)
More is Less: Inducing Sparsity via Overparameterization
by: Chou, Hung-Hsu, et al.
Published: (2021)
by: Chou, Hung-Hsu, et al.
Published: (2021)
Group Projected Subspace Pursuit for Block Sparse Signal Reconstruction: Convergence Analysis and Applications
by: He, Roy Y., et al.
Published: (2024)
by: He, Roy Y., et al.
Published: (2024)
Geometry, Computation, and Optimality in Stochastic Optimization
by: Cheng, Chen, et al.
Published: (2019)
by: Cheng, Chen, et al.
Published: (2019)
Wasserstein Distributionally Robust Estimation in High Dimensions: Performance Analysis and Optimal Hyperparameter Tuning
by: Aolaritei, Liviu, et al.
Published: (2022)
by: Aolaritei, Liviu, et al.
Published: (2022)
Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL
by: Zurek, Matthew, et al.
Published: (2025)
by: Zurek, Matthew, et al.
Published: (2025)
Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent
by: Yang, Tong, et al.
Published: (2025)
by: Yang, Tong, et al.
Published: (2025)
In-Context Learning with Representations: Contextual Generalization of Trained Transformers
by: Yang, Tong, et al.
Published: (2024)
by: Yang, Tong, et al.
Published: (2024)
Accelerating Convergence of Score-Based Diffusion Models, Provably
by: Li, Gen, et al.
Published: (2024)
by: Li, Gen, et al.
Published: (2024)
Accelerating Regularized Attention Kernel Regression for Spectrum Cartography
by: Tao, Liping, et al.
Published: (2026)
by: Tao, Liping, et al.
Published: (2026)
Statistical and Algorithmic Foundations of Reinforcement Learning
by: Chi, Yuejie, et al.
Published: (2025)
by: Chi, Yuejie, et al.
Published: (2025)
Similar Items
-
Learning to Optimize by Differentiable Programming
by: Tao, Liping, et al.
Published: (2026) -
Finite-Time Minimax Bounds and an Optimal Lyapunov Policy in Queueing Control
by: Liu, Yujie, et al.
Published: (2025) -
Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods
by: Li, Gen, et al.
Published: (2023) -
A Single-Loop First-Order Algorithm for Linearly Constrained Bilevel Optimization
by: Shen, Wei, et al.
Published: (2025) -
Generalized Orthogonal Procrustes Problem under Arbitrary Adversaries
by: Ling, Shuyang
Published: (2021)