The Hidden Cost of Approximation in Online Mirror Descent
Fuente:
arXiv
Saved in:
| Main Authors: | Schlisselberg, Ofir, Sherman, Uri, Koren, Tomer, Mansour, Yishay |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
by: Sherman, Uri, et al.
Published: (2025)
by: Sherman, Uri, et al.
Published: (2025)
Convergence and Sample Complexity of First-Order Methods for Agnostic Reinforcement Learning
by: Sherman, Uri, et al.
Published: (2025)
by: Sherman, Uri, et al.
Published: (2025)
Online Learning in MDPs with Partially Adversarial Transitions and Losses
by: Schlisselberg, Ofir, et al.
Published: (2026)
by: Schlisselberg, Ofir, et al.
Published: (2026)
Rate-Optimal Policy Optimization for Linear Markov Decision Processes
by: Sherman, Uri, et al.
Published: (2023)
by: Sherman, Uri, et al.
Published: (2023)
Collaborating in Multi-Armed Bandits with Strategic Agents
by: Barnea, Idan, et al.
Published: (2026)
by: Barnea, Idan, et al.
Published: (2026)
Regret Minimization and Convergence to Equilibria in General-sum Markov Games
by: Erez, Liad, et al.
Published: (2022)
by: Erez, Liad, et al.
Published: (2022)
Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback
by: Schlisselberg, Ofir, et al.
Published: (2025)
by: Schlisselberg, Ofir, et al.
Published: (2025)
Delay as Payoff in MAB
by: Schlisselberg, Ofir, et al.
Published: (2024)
by: Schlisselberg, Ofir, et al.
Published: (2024)
Cost-Aware Learning
by: Mohri, Clara, et al.
Published: (2026)
by: Mohri, Clara, et al.
Published: (2026)
The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2024)
by: Schliserman, Matan, et al.
Published: (2024)
Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
by: Attia, Amit, et al.
Published: (2025)
by: Attia, Amit, et al.
Published: (2025)
The impact of allocation strategies in subset learning on the expressive power of neural networks
by: Schlisselberg, Ofir, et al.
Published: (2025)
by: Schlisselberg, Ofir, et al.
Published: (2025)
The Real Price of Bandit Information in Multiclass Classification
by: Erez, Liad, et al.
Published: (2024)
by: Erez, Liad, et al.
Published: (2024)
Fast Rates for Bandit PAC Multiclass Classification
by: Erez, Liad, et al.
Published: (2024)
by: Erez, Liad, et al.
Published: (2024)
Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification
by: Schliserman, Matan, et al.
Published: (2025)
by: Schliserman, Matan, et al.
Published: (2025)
Faster Stochastic Optimization with Arbitrary Delays via Asynchronous Mini-Batching
by: Attia, Amit, et al.
Published: (2024)
by: Attia, Amit, et al.
Published: (2024)
Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback
by: Lancewicki, Tal, et al.
Published: (2025)
by: Lancewicki, Tal, et al.
Published: (2025)
Sample Complexity of Agnostic Multiclass Classification: Natarajan Dimension Strikes Back
by: Cohen, Alon, et al.
Published: (2025)
by: Cohen, Alon, et al.
Published: (2025)
The Sample Complexity of Multiclass and Sparse Contextual Bandits
by: Erez, Liad, et al.
Published: (2026)
by: Erez, Liad, et al.
Published: (2026)
Bayesian Perspective on Memorization and Reconstruction
by: Kaplan, Haim, et al.
Published: (2025)
by: Kaplan, Haim, et al.
Published: (2025)
Optimal Rates in Continual Linear Regression via Increasing Regularization
by: Levinstein, Ran, et al.
Published: (2025)
by: Levinstein, Ran, et al.
Published: (2025)
From Continual Learning to SGD and Back: Better Rates for Continual Linear Models
by: Evron, Itay, et al.
Published: (2025)
by: Evron, Itay, et al.
Published: (2025)
Probably Approximately Precision and Recall Learning
by: Cohen, Lee, et al.
Published: (2024)
by: Cohen, Lee, et al.
Published: (2024)
Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization
by: Vansover-Hager, Shira, et al.
Published: (2025)
by: Vansover-Hager, Shira, et al.
Published: (2025)
Rising Rested MAB with Linear Drift
by: Amichay, Omer, et al.
Published: (2025)
by: Amichay, Omer, et al.
Published: (2025)
Optimal Regret for Policy Optimization in Contextual Bandits
by: Levy, Orin, et al.
Published: (2026)
by: Levy, Orin, et al.
Published: (2026)
Non-stochastic Bandits With Evolving Observations
by: Bar-On, Yogev, et al.
Published: (2024)
by: Bar-On, Yogev, et al.
Published: (2024)
Online Set Learning from Precision and Recall Feedback
by: Cohen, Lee, et al.
Published: (2026)
by: Cohen, Lee, et al.
Published: (2026)
Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback
by: Levy, Orin, et al.
Published: (2025)
by: Levy, Orin, et al.
Published: (2025)
Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation
by: Levy, Orin, et al.
Published: (2026)
by: Levy, Orin, et al.
Published: (2026)
Complexity of Vector-valued Prediction: From Linear Models to Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2024)
by: Schliserman, Matan, et al.
Published: (2024)
How to Boost Any Loss Function
by: Nock, Richard, et al.
Published: (2024)
by: Nock, Richard, et al.
Published: (2024)
Learning Rate Annealing Improves Tuning Robustness in Stochastic Optimization
by: Attia, Amit, et al.
Published: (2025)
by: Attia, Amit, et al.
Published: (2025)
From Contextual Combinatorial Semi-Bandits to Bandit List Classification: Improved Sample Complexity with Sparse Rewards
by: Erez, Liad, et al.
Published: (2025)
by: Erez, Liad, et al.
Published: (2025)
How Free is Parameter-Free Stochastic Optimization?
by: Attia, Amit, et al.
Published: (2024)
by: Attia, Amit, et al.
Published: (2024)
The Horizon Threshold in Cooperative Multi-Agent Reward-Free Exploration
by: Barnea, Idan, et al.
Published: (2026)
by: Barnea, Idan, et al.
Published: (2026)
Batch Ensemble for Variance Dependent Regret in Stochastic Bandits
by: Cassel, Asaf, et al.
Published: (2024)
by: Cassel, Asaf, et al.
Published: (2024)
Individual Regret in Cooperative Stochastic Multi-Armed Bandits
by: Barnea, Idan, et al.
Published: (2024)
by: Barnea, Idan, et al.
Published: (2024)
Theoretical Foundations and Effective Algorithms for Policy-Aware Simulator Learning
by: Dann, Christoph, et al.
Published: (2026)
by: Dann, Christoph, et al.
Published: (2026)
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability
by: Attias, Idan, et al.
Published: (2022)
by: Attias, Idan, et al.
Published: (2022)
Similar Items
-
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
by: Sherman, Uri, et al.
Published: (2025) -
Convergence and Sample Complexity of First-Order Methods for Agnostic Reinforcement Learning
by: Sherman, Uri, et al.
Published: (2025) -
Online Learning in MDPs with Partially Adversarial Transitions and Losses
by: Schlisselberg, Ofir, et al.
Published: (2026) -
Rate-Optimal Policy Optimization for Linear Markov Decision Processes
by: Sherman, Uri, et al.
Published: (2023) -
Collaborating in Multi-Armed Bandits with Strategic Agents
by: Barnea, Idan, et al.
Published: (2026)