activity
20182022
most citedQuantum Wasserstein Generative Adversarial Networks

54 citations · 84 across the 6 of their papers we have counts for

collaborators
Showing quant-phShow all

8 papers · 1 filter

quant-ph2022

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…

quant-ph2022

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…

quant-ph2021

Quantum query complexity with matrix-vector products

Andrew M. Childs, Shih-Han Hung, Tongyang Li

We study quantum algorithms that learn properties of a matrix using queries that return its action on an input vector. We show that for various problems, including computing the tr…

quant-ph20201 cited

Sublinear classical and quantum algorithms for general matrix games

Tongyang Li, Chunhao Wang, Shouvanik Chakrabarti +1

We investigate sublinear classical and quantum algorithms for matrix games, a fundamental problem in optimization and machine learning, with provable guarantees. Given a matrix $A\…

quant-ph201954 cited

Quantum Wasserstein Generative Adversarial Networks

Shouvanik Chakrabarti, Yiming Huang, Tongyang Li +2

The study of quantum generative models is well-motivated, not only because of its importance in quantum machine learning and quantum chemistry but also because of the perspective o…

quant-ph201927 cited

Sublinear quantum algorithms for training linear and kernel-based classifiers

Tongyang Li, Shouvanik Chakrabarti, Xiaodi Wu

We investigate quantum algorithms for classification, a fundamental problem in machine learning, with provable guarantees. Given -dimensional data points, the state-of-the-a…