Capacity-Constrained Online Learning with Delays: Scheduling Frameworks and Regret Trade-offs
Fuente:
arXiv
Saved in:
| Main Authors: | Ryabchenko, Alexander, Attias, Idan, Roy, Daniel M. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Reduction from Delayed to Immediate Feedback for Online Convex Optimization with Improved Guarantees
by: Ryabchenko, Alexander, et al.
Published: (2026)
by: Ryabchenko, Alexander, et al.
Published: (2026)
Regret-Oracle Complexity Tradeoffs in Agnostic Online Learning
by: Attias, Idan, et al.
Published: (2026)
by: Attias, Idan, et al.
Published: (2026)
Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood
by: Liu, Ziyi, et al.
Published: (2024)
by: Liu, Ziyi, et al.
Published: (2024)
Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals
by: Liu, Ziyi, et al.
Published: (2024)
by: Liu, Ziyi, et al.
Published: (2024)
Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning
by: Attias, Idan, et al.
Published: (2025)
by: Attias, Idan, et al.
Published: (2025)
Adversarially Robust PAC Learnability of Real-Valued Functions
by: Attias, Idan, et al.
Published: (2022)
by: Attias, Idan, et al.
Published: (2022)
Online Tensor Learning: Computational and Statistical Trade-offs, Adaptivity and Optimal Regret
by: Li, Jingyang, et al.
Published: (2023)
by: Li, Jingyang, et al.
Published: (2023)
Optimal Learners for Realizable Regression: PAC Learning and Online Learning
by: Attias, Idan, et al.
Published: (2023)
by: Attias, Idan, et al.
Published: (2023)
Sample Compression Scheme Reductions
by: Attias, Idan, et al.
Published: (2024)
by: Attias, Idan, et al.
Published: (2024)
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability
by: Attias, Idan, et al.
Published: (2022)
by: Attias, Idan, et al.
Published: (2022)
Learning-Augmented Algorithms for Boolean Satisfiability
by: Attias, Idan, et al.
Published: (2025)
by: Attias, Idan, et al.
Published: (2025)
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization
by: Attias, Idan, et al.
Published: (2024)
by: Attias, Idan, et al.
Published: (2024)
Positive Distribution Shift as a Framework for Understanding Tractable Learning
by: Medvedev, Marko, et al.
Published: (2026)
by: Medvedev, Marko, et al.
Published: (2026)
Reinforcement Learning with Action-Triggered Observations
by: Ryabchenko, Alexander, et al.
Published: (2025)
by: Ryabchenko, Alexander, et al.
Published: (2025)
On the Hardness of Learning Regular Expressions
by: Attias, Idan, et al.
Published: (2025)
by: Attias, Idan, et al.
Published: (2025)
On Bits and Bandits: Quantifying the Regret-Information Trade-off
by: Shufaro, Itai, et al.
Published: (2024)
by: Shufaro, Itai, et al.
Published: (2024)
On Traceability in $\ell_p$ Stochastic Convex Optimization
by: Voitovych, Sasha, et al.
Published: (2025)
by: Voitovych, Sasha, et al.
Published: (2025)
Online Experimental Design With Estimation-Regret Trade-off Under Network Interference
by: Zhang, Zhiheng, et al.
Published: (2024)
by: Zhang, Zhiheng, 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)
Truly No-Regret Learning in Constrained MDPs
by: Müller, Adrian, et al.
Published: (2024)
by: Müller, Adrian, et al.
Published: (2024)
Agnostic Sample Compression Schemes for Regression
by: Attias, Idan, et al.
Published: (2018)
by: Attias, Idan, et al.
Published: (2018)
Online Learning of Neural Networks
by: Daniely, Amit, et al.
Published: (2025)
by: Daniely, Amit, et al.
Published: (2025)
Universal Dynamic Regret and Constraint Violation Bounds for Constrained Online Convex Optimization
by: Supantha, Subhamon, et al.
Published: (2025)
by: Supantha, Subhamon, et al.
Published: (2025)
Capacity-Constrained Continual Learning
by: Wen, Zheng, et al.
Published: (2025)
by: Wen, Zheng, et al.
Published: (2025)
PAC Learning with Improvements
by: Attias, Idan, et al.
Published: (2025)
by: Attias, Idan, et al.
Published: (2025)
Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret
by: Hu, Bingshan, et al.
Published: (2025)
by: Hu, Bingshan, et al.
Published: (2025)
RL's Razor: Why Online Reinforcement Learning Forgets Less
by: Shenfeld, Idan, et al.
Published: (2025)
by: Shenfeld, Idan, et al.
Published: (2025)
Logarithmic Regret for Online KL-Regularized Reinforcement Learning
by: Zhao, Heyang, et al.
Published: (2025)
by: Zhao, Heyang, et al.
Published: (2025)
Gradient-Variation Regret Bounds for Unconstrained Online Learning
by: Zhao, Yuheng, et al.
Published: (2026)
by: Zhao, Yuheng, et al.
Published: (2026)
Regret Distribution in Stochastic Bandits: Optimal Trade-off between Expectation and Tail Risk
by: Simchi-Levi, David, et al.
Published: (2023)
by: Simchi-Levi, David, et al.
Published: (2023)
A Theory of Online Learning with Autoregressive Chain-of-Thought Reasoning
by: Doron-Arad, Ilan, et al.
Published: (2026)
by: Doron-Arad, Ilan, et al.
Published: (2026)
Best-of-N through the Smoothing Lens: KL Divergence and Regret Analysis
by: Aminian, Gholamali, et al.
Published: (2025)
by: Aminian, Gholamali, et al.
Published: (2025)
Polyhedral Instability Governs Regret in Online Learning
by: Li, Yuetai, et al.
Published: (2026)
by: Li, Yuetai, et al.
Published: (2026)
Information Capacity Regret Bounds for Bandits with Mediator Feedback
by: Eldowa, Khaled, et al.
Published: (2024)
by: Eldowa, Khaled, et al.
Published: (2024)
Improved Regret for Bandit Convex Optimization with Delayed Feedback
by: Wan, Yuanyu, et al.
Published: (2024)
by: Wan, Yuanyu, et al.
Published: (2024)
A Regret Analysis of Bilateral Trade
by: Cesa-Bianchi, Nicolò, et al.
Published: (2021)
by: Cesa-Bianchi, Nicolò, et al.
Published: (2021)
Data-Dependent Regret Bounds for Constrained MABs
by: Genalti, Gianmarco, et al.
Published: (2025)
by: Genalti, Gianmarco, et al.
Published: (2025)
Improved Kernel Alignment Regret Bound for Online Kernel Learning
by: Li, Junfan, et al.
Published: (2022)
by: Li, Junfan, et al.
Published: (2022)
Learning-Augmented Online Scheduling with Parsimonious Preemption
by: Blue, Mugen, et al.
Published: (2026)
by: Blue, Mugen, et al.
Published: (2026)
Regret Analysis of Policy Optimization over Submanifolds for Linearly Constrained Online LQG
by: Chang, Ting-Jui, et al.
Published: (2024)
by: Chang, Ting-Jui, et al.
Published: (2024)
Similar Items
-
A Reduction from Delayed to Immediate Feedback for Online Convex Optimization with Improved Guarantees
by: Ryabchenko, Alexander, et al.
Published: (2026) -
Regret-Oracle Complexity Tradeoffs in Agnostic Online Learning
by: Attias, Idan, et al.
Published: (2026) -
Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood
by: Liu, Ziyi, et al.
Published: (2024) -
Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals
by: Liu, Ziyi, et al.
Published: (2024) -
Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning
by: Attias, Idan, et al.
Published: (2025)