12 citations · 22 across the 13 of their papers we have counts for
13 papers
The Simple Strategy-Iteration Method is Strongly Polynomial for the Turn-Based Deterministic Forward Game
Sanyou Mei, Chunlin Sun, Yinyu Ye
We study Turn-Based Deterministic Forward Games (TBDFGs), the subclass of turn-based deterministic zero-sum games in which no directed cycle contains actions controlled by both pla…
Beyond Regret: Decoupling Learning and Decision-making in Online Linear Programming
Wenzhi Gao, Dongdong Ge, Chenyu Xue +2
Online linear programming plays an important role in both revenue management and resource allocation, and recent research has focused on developing efficient first-order online lea…
Spatial Supply Repositioning with Censored Demand Data
Hansheng Jiang, Chunlin Sun, Zuo-Jun Max Shen
We consider a network inventory system motivated by one-way, on-demand vehicle sharing services. Under uncertain and correlated network demand, the service operator periodically re…
Decoupling Learning and Decision-Making: Breaking the Barrier in Online Resource Allocation with First-Order Methods
Wenzhi Gao, Chunlin Sun, Chenyu Xue +2
Online linear programming plays an important role in both revenue management and resource allocation, and recent research has focused on developing efficient first-order online lea…
Learning to Make Adherence-Aware Advice
Guanting Chen, Xiaocheng Li, Chunlin Sun +1
As artificial intelligence (AI) systems play an increasingly prominent role in human decision-making, challenges surface in the realm of human-AI interactions. One challenge arises…
When No-Rejection Learning is Consistent for Regression with Rejection
Xiaocheng Li, Shang Liu, Chunlin Sun +1
Learning with rejection has been a prototypical model for studying the human-AI interaction on prediction tasks. Upon the arrival of a sample instance, the model first uses a rejec…
Predict-then-Calibrate: A New Perspective of Robust Contextual LP
Chunlin Sun, Linyu Liu, Xiaocheng Li
Contextual optimization, also known as predict-then-optimize or prescriptive analytics, considers an optimization problem with the presence of covariates (context or side informati…
Maximum Optimality Margin: A Unified Approach for Contextual Linear Programming and Inverse Linear Programming
Chunlin Sun, Shang Liu, Xiaocheng Li
In this paper, we study the predict-then-optimize problem where the output of a machine learning prediction task is used as the input of some downstream optimization problem, say,…
Learning from Stochastically Revealed Preference
John R. Birge, Xiaocheng Li, Chunlin Sun
We study the learning problem of revealed preference in a stochastic setting: a learner observes the utility-maximizing actions of a set of agents whose utility follows some unknow…
An Adaptive State Aggregation Algorithm for Markov Decision Processes
Guanting Chen, Johann Demetrio Gaebler, Matt Peng +2
Value iteration is a well-known method of solving Markov Decision Processes (MDPs) that is simple to implement and boasts strong theoretical convergence guarantees. However, the co…
Solving Linear Programs with Fast Online Learning Algorithms
Wenzhi Gao, Dongdong Ge, Chunlin Sun +1
This paper presents fast first-order methods for solving linear programs (LPs) approximately. We adapt online linear programming algorithms to offline LPs and obtain algorithms tha…
The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
Xiaocheng Li, Chunlin Sun, Yinyu Ye
In this paper, we study the bandits with knapsacks (BwK) problem and develop a primal-dual based algorithm that achieves a problem-dependent logarithmic regret bound. The BwK probl…
Simple and Fast Algorithm for Binary Integer and Online Linear Programming
Xiaocheng Li, Chunlin Sun, Yinyu Ye
In this paper, we develop a simple and fast online algorithm for solving a class of binary integer linear programs (LPs) arisen in general resource allocation problem. The algorith…