Adversarial Online Learning with Temporal Feedback Graphs
Fuente:
arXiv
Saved in:
| Main Authors: | Gatmiry, Khashayar, Schneider, Jon |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Computing Optimal Regularizers for Online Linear Optimization
by: Gatmiry, Khashayar, et al.
Published: (2024)
by: Gatmiry, Khashayar, et al.
Published: (2024)
Learning Mixtures of Gaussians Using Diffusion Models
by: Gatmiry, Khashayar, et al.
Published: (2024)
by: Gatmiry, Khashayar, et al.
Published: (2024)
High-accuracy and dimension-free sampling with diffusions
by: Gatmiry, Khashayar, et al.
Published: (2026)
by: Gatmiry, Khashayar, et al.
Published: (2026)
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
by: Chen, Yuansi, et al.
Published: (2023)
by: Chen, Yuansi, et al.
Published: (2023)
A Unified Approach to Controlling Implicit Regularization via Mirror Descent
by: Sun, Haoyuan, et al.
Published: (2023)
by: Sun, Haoyuan, et al.
Published: (2023)
Near-Optimal Algorithms for Group Distributionally Robust Optimization and Beyond
by: Soma, Tasuku, et al.
Published: (2022)
by: Soma, Tasuku, et al.
Published: (2022)
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
by: Gatmiry, Khashayar, et al.
Published: (2024)
by: Gatmiry, Khashayar, et al.
Published: (2024)
Simplicity Bias via Global Convergence of Sharpness Minimization
by: Gatmiry, Khashayar, et al.
Published: (2024)
by: Gatmiry, Khashayar, et al.
Published: (2024)
On the Role of Depth and Looping for In-Context Learning with Task Diversity
by: Gatmiry, Khashayar, et al.
Published: (2024)
by: Gatmiry, Khashayar, et al.
Published: (2024)
What does guidance do? A fine-grained analysis in a simple setting
by: Chidambaram, Muthu, et al.
Published: (2024)
by: Chidambaram, Muthu, et al.
Published: (2024)
Cooperative Online Learning with Feedback Graphs
by: Cesa-Bianchi, Nicolò, et al.
Published: (2021)
by: Cesa-Bianchi, Nicolò, et al.
Published: (2021)
Online Learning with Bounded Recall
by: Schneider, Jon, et al.
Published: (2022)
by: Schneider, Jon, et al.
Published: (2022)
Learning on the Edge: Online Learning with Stochastic Feedback Graphs
by: Esposito, Emmanuel, et al.
Published: (2022)
by: Esposito, Emmanuel, et al.
Published: (2022)
Online Conformal Abstention for Factuality Control Under Adversarial Bandit Feedback
by: Lee, Minjae, et al.
Published: (2025)
by: Lee, Minjae, et al.
Published: (2025)
Partial Feedback Online Learning
by: Shao, Shihao, et al.
Published: (2026)
by: Shao, Shihao, et al.
Published: (2026)
Adversarial Combinatorial Semi-bandits with Graph Feedback
by: Wen, Yuxiao
Published: (2025)
by: Wen, Yuxiao
Published: (2025)
Online Conformal Prediction with Adversarial Semi-bandit Feedback via Regret Minimization
by: Yang, Junyoung, et al.
Published: (2026)
by: Yang, Junyoung, et al.
Published: (2026)
Online Learning with Multiple Fairness Regularizers via Graph-Structured Feedback
by: Zhou, Quan, et al.
Published: (2025)
by: Zhou, Quan, et al.
Published: (2025)
Online Learning with Set-Valued Feedback
by: Raman, Vinod, et al.
Published: (2023)
by: Raman, Vinod, et al.
Published: (2023)
Multi-model Online Conformal Prediction with Graph-Structured Feedback
by: Hajihashemi, Erfan, et al.
Published: (2025)
by: Hajihashemi, Erfan, et al.
Published: (2025)
Learning in an Echo Chamber: Online Learning with Replay Adversary
by: Dmitriev, Daniil, et al.
Published: (2025)
by: Dmitriev, Daniil, et al.
Published: (2025)
Online Adversarial Knowledge Distillation for Graph Neural Networks
by: Wang, Can, et al.
Published: (2021)
by: Wang, Can, et al.
Published: (2021)
Online Set Learning from Precision and Recall Feedback
by: Cohen, Lee, et al.
Published: (2026)
by: Cohen, Lee, et al.
Published: (2026)
Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries
by: Maiti, Arnab, et al.
Published: (2025)
by: Maiti, Arnab, et al.
Published: (2025)
A New Benchmark for Online Learning with Budget-Balancing Constraints
by: Braverman, Mark, et al.
Published: (2025)
by: Braverman, Mark, et al.
Published: (2025)
Distributionally-Constrained Adversaries in Online Learning
by: Blanchard, Moïse, et al.
Published: (2025)
by: Blanchard, Moïse, 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)
ARIEL: Adversarial Graph Contrastive Learning
by: Feng, Shengyu, et al.
Published: (2022)
by: Feng, Shengyu, et al.
Published: (2022)
DFORD: Directional Feedback based Online Ordinal Regression Learning
by: Manwani, Naresh, et al.
Published: (2025)
by: Manwani, Naresh, et al.
Published: (2025)
Online Continual Graph Learning
by: Donghi, Giovanni, et al.
Published: (2025)
by: Donghi, Giovanni, et al.
Published: (2025)
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
by: Zhao, Boxin, et al.
Published: (2021)
by: Zhao, Boxin, et al.
Published: (2021)
Temporal Analysis of Adversarial Attacks in Federated Learning
by: Mapakshi, Rohit, et al.
Published: (2025)
by: Mapakshi, Rohit, et al.
Published: (2025)
Adversarial Online Collaborative Filtering
by: Pasteris, Stephen, et al.
Published: (2023)
by: Pasteris, Stephen, et al.
Published: (2023)
Data-dependent Exploration for Online Reinforcement Learning from Human Feedback
by: Zhang, Zhen-Yu, et al.
Published: (2026)
by: Zhang, Zhen-Yu, et al.
Published: (2026)
Efficient Learning-based Graph Simulation for Temporal Graphs
by: Xiang, Sheng, et al.
Published: (2025)
by: Xiang, Sheng, et al.
Published: (2025)
Contextual Online Uncertainty-Aware Preference Learning for Human Feedback
by: Lu, Nan, et al.
Published: (2025)
by: Lu, Nan, et al.
Published: (2025)
Online Detection of Anomalies in Temporal Knowledge Graphs with Interpretability
by: Zhang, Jiasheng, et al.
Published: (2024)
by: Zhang, Jiasheng, et al.
Published: (2024)
Private Online Learning against an Adaptive Adversary: Realizable and Agnostic Settings
by: Li, Bo, et al.
Published: (2025)
by: Li, Bo, et al.
Published: (2025)
Optimal cross-learning for contextual bandits with unknown context distributions
by: Schneider, Jon, et al.
Published: (2024)
by: Schneider, Jon, et al.
Published: (2024)
Online Iterative Reinforcement Learning from Human Feedback with General Preference Model
by: Ye, Chenlu, et al.
Published: (2024)
by: Ye, Chenlu, et al.
Published: (2024)
Similar Items
-
Computing Optimal Regularizers for Online Linear Optimization
by: Gatmiry, Khashayar, et al.
Published: (2024) -
Learning Mixtures of Gaussians Using Diffusion Models
by: Gatmiry, Khashayar, et al.
Published: (2024) -
High-accuracy and dimension-free sampling with diffusions
by: Gatmiry, Khashayar, et al.
Published: (2026) -
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
by: Chen, Yuansi, et al.
Published: (2023) -
A Unified Approach to Controlling Implicit Regularization via Mirror Descent
by: Sun, Haoyuan, et al.
Published: (2023)