6 papers
Estimation, Prediction, and Assortment Optimization for Markov Chain Choice Models with Panel Data
Yalcin Akcay, Gerardo Berbeglia, Young-San Lin
We propose a framework for the Markov chain (MC) choice model with panel data, including parameter estimation, personalized choice prediction, and personalized assortment optimizat…
Matching with Committee Preferences
Haoyu Song, Thanh Nguyen, Young-san Lin
We study a many-to-one matching model inspired by school choice, where schools evaluate applicants using multiple rankings rather than a single priority order. We model each school…
Improved and Parameterized Algorithms for Online Multi-level Aggregation: A Memory-based Approach
Alexander Turoczy, Young-San Lin
We study the online multi-level aggregation problem with deadlines (MLAP-D) introduced by Bienkowski et al. (ESA 2016, OR 2020). In this problem, requests arrive over time at the v…
Routing-Controlled Spanners
Elena Grigorescu, Nithish Kumar Kumar, Young-San Lin
Designing sparse directed spanners, which are subgraphs that approximately maintain distance constraints, has attracted sustained interest in TCS, especially due to their wide appl…
A few good choices
Thanh Nguyen, Haoyu Song, Young-San Lin
A Condorcet winning set addresses the Condorcet paradox by selecting a few candidates--rather than a single winner--such that no unselected alternative is preferred to all of them…
Learning-Augmented Algorithms for Online Concave Packing and Convex Covering Problems
Elena Grigorescu, Young-San Lin, Maoyuan Song
Learning-augmented algorithms have been extensively studied across the computer science community in the recent years, driven by advances in machine learning predictors, which can…