:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Dean, Sarah, Curmei, Mihaela, Ratliff, Lillian J., Morgenstern, Jamie, Fazel, Maryam
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Computer Science and Game Theory
Online Access:	https://arxiv.org/abs/2206.02667
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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
by: Maiti, Arnab, et al.
Published: (2026)

On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games under Noisy Feedback
by: Maiti, Arnab, et al.
Published: (2023)

Initializing Services in Interactive ML Systems for Diverse Users
by: Bose, Avinandan, et al.
Published: (2023)

Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation
by: Liu, Junyan, 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)

On the Universal Near Optimality of Hedge in Combinatorial Settings
by: Fan, Zhiyuan, et al.
Published: (2025)

Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
by: Liu, Junyan, et al.
Published: (2025)

A Learning Algorithm That Attains the Human Optimum in a Repeated Human-Machine Interaction Game
by: Isa, Jason T., et al.
Published: (2025)

Strategically Robust Multi-Agent Reinforcement Learning with Linear Function Approximation
by: Gonzales, Jake, et al.
Published: (2026)

Convergence of Learning Dynamics in Stackelberg Games
by: Fiez, Tanner, et al.
Published: (2019)

T-TAMER: Provably Taming Trade-offs in ML Serving
by: Yang, Yuanyuan, et al.
Published: (2025)

Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality
by: Liu, Junyan, et al.
Published: (2025)

Convergence Analysis of Gradient-Based Learning with Non-Uniform Learning Rates in Non-Cooperative Multi-Agent Settings
by: Chasnov, Benjamin, et al.
Published: (2019)

Learning Optimal Tax Design in Nonatomic Congestion Games
by: Cui, Qiwen, et al.
Published: (2024)

Offline congestion games: How feedback type affects data coverage requirement
by: Jiang, Haozhe, et al.
Published: (2022)

Maximizing utility in multi-agent environments by anticipating the behavior of other learners
by: Assos, Angelos, et al.
Published: (2024)

Structure from Strategic Interaction & Uncertainty: Risk Sensitive Games for Robust Preference Learning
by: Horwitz, Max, et al.
Published: (2026)

Query-Efficient Algorithm to Find all Nash Equilibria in a Two-Player Zero-Sum Matrix Game
by: Maiti, Arnab, et al.
Published: (2023)

A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
by: Jiang, Haozhe, et al.
Published: (2023)

Strategic Usage in a Multi-Learner Setting
by: Shekhtman, Eliot, et al.
Published: (2024)

Learning in Zero-Sum Markov Games: Relaxing Strong Reachability and Mixing Time Assumptions
by: Ouhamma, Reda, et al.
Published: (2023)

Shapley Value Approximation Based on k-Additive Games
by: Pelegrina, Guilherme Dean, et al.
Published: (2025)

Emergent Alignment via Competition
by: Collina, Natalie, et al.
Published: (2025)

A survey on multi-player bandits
by: Boursier, Etienne, et al.
Published: (2022)

Accounting for AI and Users Shaping One Another: The Role of Mathematical Models
by: Dean, Sarah, et al.
Published: (2024)

Policy Design for Two-sided Platforms with Participation Dynamics
by: Kiyohara, Haruka, et al.
Published: (2025)

Improved learning rates in multi-unit uniform price auctions
by: Potfer, Marius, et al.
Published: (2025)

Markovian Pandora's box
by: Yang, Yuanyuan, et al.
Published: (2025)

Group-wise oracle-efficient algorithms for online multi-group learning
by: Deng, Samuel, et al.
Published: (2024)

"Calibeating": Beating Forecasters at Their Own Game
by: Foster, Dean P., et al.
Published: (2022)

Independent Learning of Nash Equilibria in Partially Observable Markov Potential Games with Decoupled Dynamics
by: Jordan, Philip, et al.
Published: (2026)

Nash Equilibria in Games with Playerwise Concave Coupling Constraints: Existence and Computation
by: Jordan, Philip, et al.
Published: (2025)

Bayes correlated equilibria, no-regret dynamics in Bayesian games, and the price of anarchy
by: Fujii, Kaito
Published: (2023)

Adaptive Contracts for Cost-Effective AI Delegation
by: Saig, Eden, et al.
Published: (2026)

Emergent Dominance Hierarchies in Reinforcement Learning Agents
by: Rachum, Ram, et al.
Published: (2024)

User Strategization and Trustworthy Algorithms
by: Cen, Sarah H., et al.
Published: (2023)

A memory-based spatial evolutionary game with the dynamic interaction between learners and profiteers
by: Pi, Bin, et al.
Published: (2024)

Do Data Valuations Make Good Data Prices?
by: Fan, Dongyang, et al.
Published: (2025)

Fundamental Limits of Game-Theoretic LLM Alignment: Smith Consistency and Preference Matching
by: Shi, Zhekun, et al.
Published: (2025)

Double Oracle Neural Architecture Search for Game Theoretic Deep Learning Models
by: Aung, Aye Phyu Phyu, et al.
Published: (2024)