On the Universal Near Optimality of Hedge in Combinatorial Settings
Fuente:
arXiv
Guardado en:
| Autores principales: | Fan, Zhiyuan, Maiti, Arnab, Jamieson, Kevin, Ratliff, Lillian J., Farina, Gabriele |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries
por: Maiti, Arnab, et al.
Publicado: (2025)
por: Maiti, Arnab, et al.
Publicado: (2025)
On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games under Noisy Feedback
por: Maiti, Arnab, et al.
Publicado: (2023)
por: Maiti, Arnab, et al.
Publicado: (2023)
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
por: Liu, Junyan, et al.
Publicado: (2025)
por: Liu, Junyan, et al.
Publicado: (2025)
Efficient Uncoupled Learning Dynamics with $\tilde{O}\!\left(T^{-1/4}\right)$ Last-Iterate Convergence in Bilinear Saddle-Point Problems over Convex Sets under Bandit Feedback
por: Maiti, Arnab, et al.
Publicado: (2026)
por: Maiti, Arnab, et al.
Publicado: (2026)
Query-Efficient Algorithm to Find all Nash Equilibria in a Two-Player Zero-Sum Matrix Game
por: Maiti, Arnab, et al.
Publicado: (2023)
por: Maiti, Arnab, et al.
Publicado: (2023)
On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games
por: Fan, Zhiyuan, et al.
Publicado: (2024)
por: Fan, Zhiyuan, et al.
Publicado: (2024)
GAE Falls Short in Imperfect-Information Self-Play Reinforcement Learning
por: Fan, Zhiyuan, et al.
Publicado: (2026)
por: Fan, Zhiyuan, et al.
Publicado: (2026)
Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation
por: Liu, Junyan, et al.
Publicado: (2026)
por: Liu, Junyan, et al.
Publicado: (2026)
Emergent specialization from participation dynamics and multi-learner retraining
por: Dean, Sarah, et al.
Publicado: (2022)
por: Dean, Sarah, et al.
Publicado: (2022)
A Learning Algorithm That Attains the Human Optimum in a Repeated Human-Machine Interaction Game
por: Isa, Jason T., et al.
Publicado: (2025)
por: Isa, Jason T., et al.
Publicado: (2025)
Strategically Robust Multi-Agent Reinforcement Learning with Linear Function Approximation
por: Gonzales, Jake, et al.
Publicado: (2026)
por: Gonzales, Jake, et al.
Publicado: (2026)
Convergence Analysis of Gradient-Based Learning with Non-Uniform Learning Rates in Non-Cooperative Multi-Agent Settings
por: Chasnov, Benjamin, et al.
Publicado: (2019)
por: Chasnov, Benjamin, et al.
Publicado: (2019)
Cautious Optimism: A Meta-Algorithm for Near-Constant Regret in General Games
por: Soleymani, Ashkan, et al.
Publicado: (2025)
por: Soleymani, Ashkan, et al.
Publicado: (2025)
Convergence of Learning Dynamics in Stackelberg Games
por: Fiez, Tanner, et al.
Publicado: (2019)
por: Fiez, Tanner, et al.
Publicado: (2019)
An Efficient Black-Box Reduction from Online Learning to Multicalibration, and a New Route to $Φ$-Regret Minimization
por: Farina, Gabriele, et al.
Publicado: (2026)
por: Farina, Gabriele, et al.
Publicado: (2026)
Online Learning and Equilibrium Computation with Ranking Feedback
por: Liu, Mingyang, et al.
Publicado: (2026)
por: Liu, Mingyang, et al.
Publicado: (2026)
Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality
por: Liu, Junyan, et al.
Publicado: (2025)
por: Liu, Junyan, et al.
Publicado: (2025)
Hedging and Approximate Truthfulness in Traditional Forecasting Competitions
por: Monroe, Mary, et al.
Publicado: (2024)
por: Monroe, Mary, et al.
Publicado: (2024)
The Stability of Online Algorithms in Performative Prediction
por: Farina, Gabriele, et al.
Publicado: (2026)
por: Farina, Gabriele, et al.
Publicado: (2026)
Optimal Correlated Equilibria in General-Sum Extensive-Form Games: Fixed-Parameter Algorithms, Hardness, and Two-Sided Column-Generation
por: Zhang, Brian, et al.
Publicado: (2022)
por: Zhang, Brian, et al.
Publicado: (2022)
Learning Safely Without Knowing the World:COMPASS-Hedge
por: Hu, Ting, et al.
Publicado: (2026)
por: Hu, Ting, et al.
Publicado: (2026)
Nearly-Optimal Bandit Learning in Stackelberg Games with Side Information
por: Balcan, Maria-Florina, et al.
Publicado: (2025)
por: Balcan, Maria-Florina, et al.
Publicado: (2025)
Optimal Rates for Feasible Payoff Set Estimation in Games
por: Barbara, Annalisa, et al.
Publicado: (2026)
por: Barbara, Annalisa, et al.
Publicado: (2026)
Faster Rates for No-Regret Learning in General Games via Cautious Optimism
por: Soleymani, Ashkan, et al.
Publicado: (2025)
por: Soleymani, Ashkan, et al.
Publicado: (2025)
LiteEFG: An Efficient Python Library for Solving Extensive-form Games
por: Liu, Mingyang, et al.
Publicado: (2024)
por: Liu, Mingyang, et al.
Publicado: (2024)
A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
por: Liu, Mingyang, et al.
Publicado: (2024)
por: Liu, Mingyang, et al.
Publicado: (2024)
Tight Regret Upper and Lower Bounds for Optimistic Hedge in Two-Player Zero-Sum Games
por: Tsuchiya, Taira
Publicado: (2025)
por: Tsuchiya, Taira
Publicado: (2025)
Structure from Strategic Interaction & Uncertainty: Risk Sensitive Games for Robust Preference Learning
por: Horwitz, Max, et al.
Publicado: (2026)
por: Horwitz, Max, et al.
Publicado: (2026)
Incentivizing Exploration with Linear Contexts and Combinatorial Actions
por: Sellke, Mark
Publicado: (2023)
por: Sellke, Mark
Publicado: (2023)
Learning and Computation of $Φ$-Equilibria at the Frontier of Tractability
por: Zhang, Brian Hu, et al.
Publicado: (2025)
por: Zhang, Brian Hu, et al.
Publicado: (2025)
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
por: Cai, Yang, et al.
Publicado: (2023)
por: Cai, Yang, et al.
Publicado: (2023)
Zeroth-Order Stackelberg Control in Combinatorial Congestion Games
por: Masiha, Saeed, et al.
Publicado: (2026)
por: Masiha, Saeed, et al.
Publicado: (2026)
A Polynomial-Time Algorithm for Variational Inequalities under the Minty Condition
por: Anagnostides, Ioannis, et al.
Publicado: (2025)
por: Anagnostides, Ioannis, et al.
Publicado: (2025)
Multi-Agent Combinatorial-Multi-Armed-Bandit framework for the Submodular Welfare Problem under Bandit Feedback
por: Pokhriyal, Subham, et al.
Publicado: (2026)
por: Pokhriyal, Subham, et al.
Publicado: (2026)
Differentially Private Equilibrium Finding in Polymatrix Games
por: Liu, Mingyang, et al.
Publicado: (2025)
por: Liu, Mingyang, et al.
Publicado: (2025)
Learning-Augmented Online Bidding in Stochastic Settings
por: Angelopoulos, Spyros, et al.
Publicado: (2025)
por: Angelopoulos, Spyros, et al.
Publicado: (2025)
Nearly Tight Regret Bounds for Profit Maximization in Bilateral Trade
por: Di Gregorio, Simone, et al.
Publicado: (2025)
por: Di Gregorio, Simone, et al.
Publicado: (2025)
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games
por: Cai, Yang, et al.
Publicado: (2024)
por: Cai, Yang, et al.
Publicado: (2024)
Optimally Installing Strict Equilibria
por: McMahan, Jeremy, et al.
Publicado: (2025)
por: McMahan, Jeremy, et al.
Publicado: (2025)
Online Generalized-mean Welfare Maximization: Achieving Near-Optimal Regret from Samples
por: Yang, Zongjun, et al.
Publicado: (2026)
por: Yang, Zongjun, et al.
Publicado: (2026)
Ejemplares similares
-
Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries
por: Maiti, Arnab, et al.
Publicado: (2025) -
On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games under Noisy Feedback
por: Maiti, Arnab, et al.
Publicado: (2023) -
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
por: Liu, Junyan, et al.
Publicado: (2025) -
Efficient Uncoupled Learning Dynamics with $\tilde{O}\!\left(T^{-1/4}\right)$ Last-Iterate Convergence in Bilinear Saddle-Point Problems over Convex Sets under Bandit Feedback
por: Maiti, Arnab, et al.
Publicado: (2026) -
Query-Efficient Algorithm to Find all Nash Equilibria in a Two-Player Zero-Sum Matrix Game
por: Maiti, Arnab, et al.
Publicado: (2023)