:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autor principal:	Zhang, Jinxiong
Formato:	Preprint
Publicado:	2021
Materias:	Machine Learning Optimization and Control
Acceso en línea:	https://arxiv.org/abs/2101.11347
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Sufficient Decision Proxies for Decision-Focused Learning
por: Schutte, Noah, et al.
Publicado: (2025)

ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription
por: Vossler, Patrick, et al.
Publicado: (2023)

Robust Losses for Decision-Focused Learning
por: Schutte, Noah, et al.
Publicado: (2023)

Decision-Focused Learning with Directional Gradients
por: Huang, Michael, et al.
Publicado: (2024)

Improving the Validity of Decision Trees as Explanations
por: Nemecek, Jiri, et al.
Publicado: (2023)

Improved Compression Bounds for Scenario Decision Making
por: Berger, Guillaume O.
Publicado: (2025)

Structured Reinforcement Learning for Combinatorial Decision-Making
por: Hoppe, Heiko, et al.
Publicado: (2025)

Learning Sequential Decisions from Multiple Sources via Group-Robust Markov Decision Processes
por: Xu, Mingyuan, et al.
Publicado: (2026)

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

Data-driven Piecewise Affine Decision Rules for Stochastic Programming with Covariate Information
por: Zhang, Yiyang, et al.
Publicado: (2023)

An Explainable and Interpretable Composite Indicator Based on Decision Rules
por: Corrente, Salvatore, et al.
Publicado: (2025)

Learning to Cover: Online Learning and Optimization with Irreversible Decisions
por: Jacquillat, Alexandre, et al.
Publicado: (2024)

Weakly Time-Coupled Approximation of Markov Decision Processes
por: Soheili, Negar, et al.
Publicado: (2026)

Online Markov Decision Processes with Terminal Law Constraints
por: Moreno, Bianca Marin, et al.
Publicado: (2026)

DistrictNet: Decision-aware learning for geographical districting
por: Ahmed, Cheikh, et al.
Publicado: (2024)

Decision-Aware Predictive Model Selection for Workforce Allocation
por: Stratman, Eric G., et al.
Publicado: (2024)

Optimal Sample Complexity for Average Reward Markov Decision Processes
por: Wang, Shengbo, et al.
Publicado: (2023)

Deceptive Sequential Decision-Making via Regularized Policy Optimization
por: Kim, Yerin, et al.
Publicado: (2025)

Decision-calibrated prediction sets for robust power system operations
por: Stratigakos, Akylas, et al.
Publicado: (2026)

Decision-Focused Federated Learning Under Heterogeneous Objectives and Constraints
por: Ziliaskopoulos, Konstantinos, et al.
Publicado: (2026)

Flipping-based Policy for Chance-Constrained Markov Decision Processes
por: Shen, Xun, et al.
Publicado: (2024)

Provably Efficient Representation Selection in Low-rank Markov Decision Processes: From Online to Offline RL
por: Zhang, Weitong, et al.
Publicado: (2021)

Online Reinforcement Learning in Markov Decision Process Using Linear Programming
por: Leon, Vincent, et al.
Publicado: (2023)

On the Robustness of Decision-Focused Learning
por: Farhat, Yehya
Publicado: (2023)

Achieving Instance-dependent Sample Complexity for Constrained Markov Decision Process
por: Jiang, Jiashuo, et al.
Publicado: (2024)

A Survey of Contextual Optimization Methods for Decision Making under Uncertainty
por: Sadana, Utsav, et al.
Publicado: (2023)

Wait-Less Offline Tuning and Re-solving for Online Decision Making
por: Sun, Jingruo, et al.
Publicado: (2024)

Learning An Interpretable Risk Scoring System for Maximizing Decision Net Benefit
por: Chi, Wenhao, et al.
Publicado: (2026)

What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimization
por: Bennouna, Omar, et al.
Publicado: (2025)

Efficient Algorithms for Robust Markov Decision Processes with $s$-Rectangular Ambiguity Sets
por: Ho, Chin Pang, et al.
Publicado: (2026)

A Reliability Theory of Compromise Decisions for Large-Scale Stochastic Programs
por: Diao, Shuotao, et al.
Publicado: (2024)

Non-stationary and Varying-discounting Markov Decision Processes for Reinforcement Learning
por: Chen, Zhizuo, et al.
Publicado: (2025)

"Over-optimizing" for Normality: Budget-constrained Uncertainty Quantification for Contextual Decision-making
por: Wang, Yanyuan, et al.
Publicado: (2025)

Accelerating Fleet Upgrade Decisions with Machine-Learning Enhanced Optimization
por: Chai, Kenrick Howin, et al.
Publicado: (2025)

Parameter-Free Algorithms for Performative Regret Minimization under Decision-Dependent Distributions
por: Park, Sungwoo, et al.
Publicado: (2024)

Safe Reinforcement Learning for Constrained Markov Decision Processes with Stochastic Stopping Time
por: Mazumdar, Abhijit, et al.
Publicado: (2024)

On Convergence of Average-Reward Q-Learning in Weakly Communicating Markov Decision Processes
por: Wan, Yi, et al.
Publicado: (2024)

Risk-sensitive Markov Decision Process and Learning under General Utility Functions
por: Wu, Zhengqi, et al.
Publicado: (2023)

PAC Learnability of Scenario Decision-Making Algorithms: Necessary Conditions and Sufficient Conditions
por: Berger, Guillaume O., et al.
Publicado: (2025)

Robustifying Conditional Portfolio Decisions via Optimal Transport
por: Nguyen, Viet Anh, et al.
Publicado: (2021)