Cover Image

Optimal Online Bookmaking for Binary Games

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bhatt, Alankrita, Ordentlich, Or, Sabag, Oron
Format:	Preprint
Published:	2025
Subjects:	Computer Science and Game Theory Information Theory Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimal Online Bookmaking for Any Number of Outcomes
by: Tal, Hadar, et al.
Published: (2025)

Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with Bandit Feedback
by: Ba, Wenjia, et al.
Published: (2021)

Optimistic Online Learning in Symmetric Cone Games
by: Barakat, Anas, et al.
Published: (2025)

Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games
by: Cai, Yang, et al.
Published: (2024)

Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback
by: Jordan, Michael I., et al.
Published: (2023)

Online Generalized-mean Welfare Maximization: Achieving Near-Optimal Regret from Samples
by: Yang, Zongjun, et al.
Published: (2026)

A Soft Inducement Framework for Incentive-Aided Steering of No-Regret Players
by: Yorulmaz, Asrin Efe, et al.
Published: (2025)

Learning How to Strategically Disclose Information
by: Velicheti, Raj Kiriti, et al.
Published: (2024)

Learning to Bid Optimally and Efficiently in Adversarial First-price Auctions
by: Han, Yanjun, et al.
Published: (2020)

The Oracle Complexity of Simplex-based Matrix Games
by: Kornowski, Guy, et al.
Published: (2024)

Convergence of Regret Matching in Potential Games and Constrained Optimization
by: Anagnostides, Ioannis, et al.
Published: (2025)

Operator Splitting for Learning to Predict Equilibria in Convex Games
by: McKenzie, Daniel, et al.
Published: (2021)

Game Theoretic Semi-Distributed D2D Resource Allocation Underlaying an LTE Network
by: Neogi, Anushree
Published: (2017)

Near-Optimal Regret-Queue Length Tradeoff in Online Learning for Two-Sided Markets
by: Yang, Zixian, et al.
Published: (2025)

Reinforcement Learning for Finite Space Mean-Field Type Games
by: Shao, Kai, et al.
Published: (2024)

Online Multi-Agent Control with Adversarial Disturbances
by: Barakat, Anas, et al.
Published: (2025)

Faster Rates for No-Regret Learning in General Games via Cautious Optimism
by: Soleymani, Ashkan, et al.
Published: (2025)

Achieving Logarithmic Regret in KL-Regularized Zero-Sum Markov Games
by: Nayak, Anupam, et al.
Published: (2025)

Small-Gain Nash: Certified Contraction to Nash Equilibria in Differentiable Games
by: Sharma, Vedansh
Published: (2025)

Satisficing Paths and Independent Multi-Agent Reinforcement Learning in Stochastic Games
by: Yongacoglu, Bora, et al.
Published: (2021)

Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
by: Cai, Yang, et al.
Published: (2024)

Finite-Sample Guarantees for Learning Dynamics in Zero-Sum Polymatrix Games
by: Faizal, Fathima Zarin, et al.
Published: (2024)

An Exponentially Converging Particle Method for the Mixed Nash Equilibrium of Continuous Games
by: Wang, Guillaume, et al.
Published: (2022)

Data-Scarce Identification of Game Dynamics via Sum-of-Squares Optimization
by: Sakos, Iosif, et al.
Published: (2023)

Mistake, Manipulation and Margin Guarantees in Online Strategic Classification
by: Shen, Lingqing, et al.
Published: (2024)

Cautious Optimism: A Meta-Algorithm for Near-Constant Regret in General Games
by: Soleymani, Ashkan, et al.
Published: (2025)

Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization
by: Daskalakis, Constantinos, et al.
Published: (2018)

Finite-Agent Stochastic Differential Games on Large Graphs: II. Graph-Based Architectures
by: Hu, Ruimeng, et al.
Published: (2025)

On Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games
by: Cai, Yang, et al.
Published: (2025)

From Average-Iterate to Last-Iterate Convergence in Games: A Reduction and Its Applications
by: Cai, Yang, et al.
Published: (2025)

Unsupervised Solution Operator Learning for Mean-Field Games via Sampling-Invariant Parametrizations
by: Huang, Han, et al.
Published: (2024)

Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies
by: Chen, Sijin, et al.
Published: (2024)

A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agents
by: Laurière, Mathieu, et al.
Published: (2024)

Last-Iterate Guarantees for Learning in Co-coercive Games
by: Chandak, Siddharth, et al.
Published: (2026)

Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games
by: Yang, Tong, et al.
Published: (2025)

Near Optimal Convergence to Coarse Correlated Equilibrium in General-Sum Markov Games
by: Yorulmaz, Asrin Efe, et al.
Published: (2025)

Strategically Robust Game Theory via Optimal Transport
by: Lanzetti, Nicolas, et al.
Published: (2025)

Optimal Pricing for Linear-Quadratic Games with Nonlinear Interaction Between Agents
by: Cai, Jiamin, et al.
Published: (2024)

Communication over LQG Control Systems: A Convex Optimization Approach to Capacity
by: Rips, Aharon, et al.
Published: (2025)

Solving Zero-Sum Convex Markov Games
by: Kalogiannis, Fivos, et al.
Published: (2025)