:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lee, Jongmin, Rakhsha, Amin, Ryu, Ernest K., Farahmand, Amir-massoud
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Optimization and Control
Accès en ligne:	https://arxiv.org/abs/2407.10454
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

PID Accelerated Temporal Difference Algorithms
par: Bedaywi, Mark, et autres
Publié: (2024)

Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
par: Lee, Jongmin, et autres
Publié: (2025)

A Truncated Newton Method for Optimal Transport
par: Kemertas, Mete, et autres
Publié: (2025)

Policy Gradient Algorithms in Average-Reward Multichain MDPs
par: Lee, Jongmin, et autres
Publié: (2026)

Majority of the Bests: Improving Best-of-N via Bootstrapping
par: Rakhsha, Amin, et autres
Publié: (2025)

LoRA Training in the NTK Regime has No Spurious Local Minima
par: Jang, Uijeong, et autres
Publié: (2024)

Convergence Analyses of Davis-Yin Splitting via Scaled Relative Graphs
par: Lee, Jongmin, et autres
Publié: (2022)

Rank-One Modified Value Iteration
par: Kolarijani, Arman Sharifi, et autres
Publié: (2025)

Deflation-Free Optimal Scoring
par: Afroz, Sharmin, et autres
Publié: (2026)

Switching-Geometry Analysis of Deflated Q-Value Iteration
par: Lee, Donghwan
Publié: (2026)

Sharpness-Aware Minimization Can Hallucinate Minimizers
par: Park, Chanwoong, et autres
Publié: (2025)

On the Error-Propagation of Inexact Hotelling's Deflation for Principal Component Analysis
par: Liao, Fangshuo, et autres
Publié: (2023)

From Optimization to Control: Quasi Policy Iteration
par: Kolarijani, Mohammad Amin Sharifi, et autres
Publié: (2023)

Finite-Time Bounds for Average-Reward Fitted Q-Iteration
par: Lee, Jongmin, et autres
Publié: (2025)

Higher-Order Newton Methods with Polynomial Work per Iteration
par: Ahmadi, Amir Ali, et autres
Publié: (2023)

Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
par: Di, Qiwei, et autres
Publié: (2023)

Differentially Private Clipped-SGD: High-Probability Convergence with Arbitrary Clipping Level
par: Khah, Saleh Vatan, et autres
Publié: (2025)

Truncated Variance Reduced Value Iteration
par: Jin, Yujia, et autres
Publié: (2024)

Provable Model-Parallel Distributed Principal Component Analysis with Parallel Deflation
par: Liao, Fangshuo, et autres
Publié: (2025)

Nesterov Flow May Travel Infinitely Long to Converge to a Minimizer
par: Ryu, Ernest K.
Publié: (2026)

Uniqueness of DRS as the 2 Operator Resolvent-Splitting and Impossibility of 3 Operator Resolvent-Splitting
par: Ryu, Ernest K.
Publié: (2018)

Probabilistic Iterative Hard Thresholding for Sparse Learning
par: Bergamaschi, Matteo, et autres
Publié: (2024)

On the Last-Iterate Convergence of Shuffling Gradient Methods
par: Liu, Zijian, et autres
Publié: (2024)

Accelerating Sinkhorn Algorithm with Sparse Newton Iterations
par: Tang, Xun, et autres
Publié: (2024)

Iterative Minimax Games with Coupled Linear Constraints
par: Zhang, Huiling, et autres
Publié: (2022)

Criteria and Bias of Parameterized Linear Regression under Edge of Stability Regime
par: Zhang, Peiyuan, et autres
Publié: (2024)

Nesterov Acceleration with Operator Decomposition
par: Lee, Jaewook, et autres
Publié: (2026)

Self-Supervised Learning of Iterative Solvers for Constrained Optimization
par: Lüken, Lukas, et autres
Publié: (2024)

Robust Sublinear Convergence Rates for Iterative Bregman Projections
par: Peyré, Gabriel
Publié: (2026)

Gradient Descent's Last Iterate is Often (slightly) Suboptimal
par: Kornowski, Guy, et autres
Publié: (2026)

Convergence Rate of the Last Iterate of Stochastic Proximal Algorithms
par: Vaidyan, Kevin Kurian Thomas, et autres
Publié: (2026)

Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
par: Liu, Zijian, et autres
Publié: (2023)

Safely Learning Dynamical Systems
par: Ahmadi, Amir Ali, et autres
Publié: (2023)

Dynamic Rolling Horizon Optimization for Network-Constrained V2X Value Stacking of Electric Vehicles Under Uncertainties
par: Jiang, Canchen, et autres
Publié: (2025)

Last Iterate Convergence of Incremental Methods and Applications in Continual Learning
par: Cai, Xufeng, et autres
Publié: (2024)

Iterative regularization in classification via hinge loss diagonal descent
par: Apidopoulos, Vassilis, et autres
Publié: (2022)

Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
par: Attia, Amit, et autres
Publié: (2025)

PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport
par: Wu, Di, et autres
Publié: (2025)

$ψ$DAG: Projected Stochastic Approximation Iteration for DAG Structure Learning
par: Ziu, Klea, et autres
Publié: (2024)

Distributionally Robust Optimization via Iterative Algorithms in Continuous Probability Spaces
par: Zhu, Linglingzhi, et autres
Publié: (2024)