:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Zhang, Jinxiong
Format:	Preprint
Published:	2021
Subjects:	Machine Learning Optimization and Control
Online Access:	https://arxiv.org/abs/2101.11347
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

On the Robustness of Decision-Focused Learning
by: Farhat, Yehya
Published: (2023)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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