From the 1 of 6 linked papers with an AI index.
6 papers
Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise
Bin Luo, Chengchang Liu, Jonathan Allcock +2
The paper proposes quantum mean estimators for heavy‑tailed random variables and uses them to design quantum stochastic gradient descent methods that achieve lower query complexity…
A Scalable Distributed Quantum Optimization Framework via Factor Graph Paradigm
Yuwen Huang, Xiaojun Lin, Bin Luo +1
Distributed quantum computing (DQC) connects many small quantum processors into a single logical machine, offering a practical route to scalable quantum computation. However, most…
Offline Clustering of Linear Bandits: The Power of Clusters under Limited Data
Jingyuan Liu, Zeyu Zhang, Xuchuang Wang +4
Contextual multi-armed bandit is a fundamental learning framework for making a sequence of decisions, e.g., advertising recommendations for a sequence of arriving users. Recent wor…
Optimal Online Probe Allocation for Classical and Quantum Network Tomography
Xuchuang Wang, Yu-Zhen Janice Chen, Matheus Guedes de Andrade +4
How to efficiently perform network tomography is a fundamental problem in network management and monitoring. A network tomography task usually consists of applying multiple probing…
Competitive Algorithms for Multi-Agent Ski-Rental Problems
Xuchuang Wang, Bo Sun, Hedyeh Beyhaghi +3
This paper introduces a novel multi-agent ski-rental problem that generalizes the classical ski-rental dilemma to a group setting where agents incur individual and shared costs. In…
Quantum Algorithms for Finite-horizon Markov Decision Processes
Bin Luo, Yuwen Huang, Jonathan Allcock +3
In this work, we design quantum algorithms that are more efficient than classical algorithms to solve time-dependent and finite-horizon Markov Decision Processes (MDPs) in two dist…