6 citations · 10 across the 7 of their papers we have counts for
7 papers
RL in Markov Games with Independent Function Approximation: Improved Sample Complexity Bound under the Local Access Model
Junyi Fan, Yuxuan Han, Jialin Zeng +4
Efficiently learning equilibria with large state and action spaces in general-sum Markov games while overcoming the curse of multi-agency is a challenging problem. Recent works hav…
Optimal Contextual Bandits with Knapsacks under Realizability via Regression Oracles
Yuxuan Han, Jialin Zeng, Yang Wang +2
We study the stochastic contextual bandit with knapsacks (CBwK) problem, where each action, taken upon a context, not only leads to a random reward but also costs a random resource…
Performance Analysis of OMP in Super-Resolution
Yuxuan Han, Zhiyi Huang, Yang Wang +1
Given a spectrally sparse signal consisting of complex sinusoids, we consider the super-resolution problem,…
On Private Online Convex Optimization: Optimal Algorithms in -Geometry and High Dimensional Contextual Bandits
Yuxuan Han, Zhicong Liang, Zhipeng Liang +3
Differentially private (DP) stochastic convex optimization (SCO) is ubiquitous in trustworthy machine learning algorithm design. This paper studies the DP-SCO problem with streamin…
OSKR/OKAI: Systematic Optimization of Key Encapsulation Mechanisms from Module Lattice
Shiyu Shen, Feng He, Zhichuang Liang +2
In this work, we make \emph{systematic} optimizations of key encapsulation mechanisms (KEM) based on module learning-with-errors (MLWE), covering algorithmic design, fundamental op…
Generalized Linear Bandits with Local Differential Privacy
Yuxuan Han, Zhipeng Liang, Yang Wang +1
Contextual bandit algorithms are useful in personalized online decision-making. However, many applications such as personalized medicine and online advertising require the utilizat…
SmartTriage: A system for personalized patient data capture, documentation generation, and decision support
Ilya Valmianski, Nave Frost, Navdeep Sood +6
Symptom checkers have emerged as an important tool for collecting symptoms and diagnosing patients, minimizing the involvement of clinical personnel. We developed a machine-learnin…