Cover Image

Parameter-Free Algorithms for Performative Regret Minimization under Decision-Dependent Distributions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Park, Sungwoo, Kwon, Junyeop, Kim, Byeongnoh, Chae, Suhyun, Lee, Jeeyong, Lee, Dabeen
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Infinite-Horizon Reinforcement Learning with Multinomial Logistic Function Approximation
by: Park, Jaehyun, et al.
Published: (2024)

Learning Weakly Communicating Average-Reward CMDPs: Strong Duality and Improved Regret
by: Yu, Kihyun, et al.
Published: (2026)

Provably Efficient Infinite-Horizon Average-Reward Reinforcement Learning with Linear Function Approximation
by: Chae, Woojin, et al.
Published: (2024)

Improved Regret Bound for Safe Reinforcement Learning via Tighter Cost Pessimism and Reward Optimism
by: Yu, Kihyun, et al.
Published: (2024)

Stochastic-Constrained Stochastic Optimization with Markovian Data
by: Kim, Yeongjong, et al.
Published: (2023)

Near-Optimal Primal-Dual Algorithm for Learning Linear Mixture CMDPs with Adversarial Rewards
by: Yu, Kihyun, et al.
Published: (2026)

Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
by: Chae, Woojin, et al.
Published: (2024)

Chebyshev Center-Based Direction Selection for Multi-Objective Optimization and Training PINNs
by: Yoon, Hoyeol, et al.
Published: (2026)

An Equivalence Between Static and Dynamic Regret Minimization
by: Jacobsen, Andrew, et al.
Published: (2024)

Wasserstein Distributionally Robust Regret Optimization
by: Fiechtner, Lukas-Benedikt, et al.
Published: (2025)

Decision-Dependent Stochastic Optimization: The Role of Distribution Dynamics
by: He, Zhiyu, et al.
Published: (2025)

Tail Distribution of Regret in Optimistic Reinforcement Learning
by: Khodadadian, Sajad, et al.
Published: (2025)

Critical Influence of Overparameterization on Sharpness-aware Minimization
by: Shin, Sungbin, et al.
Published: (2023)

Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
by: Tran-The, Hung, et al.
Published: (2022)

Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization
by: Dubois-Taine, Benjamin, et al.
Published: (2022)

Completely Parameter-Free Single-Loop Algorithms for Nonconvex-Concave Minimax Problems
by: Yang, Junnan, et al.
Published: (2024)

Parameter-Free Non-Ergodic Extragradient Algorithms for Solving Monotone Variational Inequalities
by: Shen, Lingqing, et al.
Published: (2026)

Online Convex Optimization with Heavy Tails: Old Algorithms, New Regrets, and Applications
by: Liu, Zijian
Published: (2025)

Beyond $\mathcal{O}(\sqrt{T})$ Regret: Decoupling Learning and Decision-making in Online Linear Programming
by: Gao, Wenzhi, et al.
Published: (2025)

Two-timescale Extragradient for Finding Local Minimax Points
by: Chae, Jiseok, et al.
Published: (2023)

How Free is Parameter-Free Stochastic Optimization?
by: Attia, Amit, et al.
Published: (2024)

Distributionally Robust Regret Optimal Control Under Moment-Based Ambiguity Sets
by: Taha, Feras Al, et al.
Published: (2025)

Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets
by: Dellaporta, Charita, et al.
Published: (2024)

Sharpness-Aware Minimization Can Hallucinate Minimizers
by: Park, Chanwoong, et al.
Published: (2025)

Making SGD Parameter-Free
by: Carmon, Yair, et al.
Published: (2022)

Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs
by: Zamir, Guy, et al.
Published: (2026)

Distributed Online Bandit Nonconvex Optimization with One-Point Residual Feedback via Dynamic Regret
by: Hua, Youqing, et al.
Published: (2024)

Optimal Algorithms for Stochastic Complementary Composite Minimization
by: d'Aspremont, Alexandre, et al.
Published: (2022)

$k$-Submodular Interdiction Problems under Distributional Risk-Receptiveness and Robustness: Application to Machine Learning
by: Park, Seonghun, et al.
Published: (2024)

Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements
by: Chae, Jiseok, et al.
Published: (2024)

Accelerated Parameter-Free Stochastic Optimization
by: Kreisler, Itai, et al.
Published: (2024)

Online Learning on Hidden-Convex Losses via Algorithmic Equivalence: Optimal Regret, Geometric Barrier, and Bandit Feedback
by: Barakat, Anas, et al.
Published: (2026)

SOREL: A Stochastic Algorithm for Spectral Risks Minimization
by: Ge, Yuze, et al.
Published: (2024)

From Contextual Data to Newsvendor Decisions: On the Actual Performance of Data-Driven Algorithms
by: Besbes, Omar, et al.
Published: (2023)

DGSAM: Domain Generalization via Individual Sharpness-Aware Minimization
by: Song, Youngjun, et al.
Published: (2025)

Problem-Parameter-Free Decentralized Bilevel Optimization
by: Zhai, Zhiwei, et al.
Published: (2025)

Sign-SGD via Parameter-Free Optimization
by: Medyakov, Daniil, et al.
Published: (2025)

Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games
by: Gao, Minbo, et al.
Published: (2023)

Regret Analysis: a control perspective
by: Gibson, Travis E., et al.
Published: (2025)

The Sample Complexity of Parameter-Free Stochastic Convex Optimization
by: Lawrence, Jared, et al.
Published: (2025)