171 citations · 480 across the 25 of their papers we have counts for
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Robustness of Quantum Algorithms for Nonconvex Optimization
Weiyuan Gong, Chenyi Zhang, Tongyang Li
Recent results suggest that quantum computers possess the potential to speed up nonconvex optimization problems. However, a crucial factor for the implementation of quantum optimiz…
Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions
Chenyi Zhang, Tongyang Li
Quantum algorithms for optimization problems are of general interest. Despite recent progress in classical lower bounds for nonconvex optimization under different settings and quan…
A Quantum Algorithm Framework for Discrete Probability Distributions with Applications to Rényi Entropy Estimation
Xinzhao Wang, Shengyu Zhang, Tongyang Li
Estimating statistical properties is fundamental in statistics and computer science. In this paper, we propose a unified quantum algorithm framework for estimating properties of di…
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants
Andrew M. Childs, Tongyang Li, Jin-Peng Liu +2
Given a convex function , the problem of sampling from a distribution is called log-concave sampling. This task has wide app…
Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits
Tongyang Li, Ruizhe Zhang
We initiate the study of quantum algorithms for optimizing approximately convex functions. Given a convex set and a function $F\colon\mathbb{R}^{n…
On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks
Yizhou Liu, Weijie J. Su, Tongyang Li
Classical algorithms are often not effective for solving nonconvex optimization problems where local minima are separated by high barriers. In this paper, we explore possible quant…
Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regrets
Zongqi Wan, Zhijie Zhang, Tongyang Li +2
Multi-arm bandit (MAB) and stochastic linear bandit (SLB) are important models in reinforcement learning, and it is well-known that classical algorithms for bandits with time horiz…
Quantum State Preparation with Optimal Circuit Depth: Implementations and Applications
Xiao-Ming Zhang, Tongyang Li, Xiao Yuan
Quantum state preparation is an important subroutine for quantum computing. We show that any -qubit quantum state can be prepared with a -depth circuit using only single-…