13 citations · 14 across the 5 of their papers we have counts for
7 papers
Metastability in Quantum Dynamics for Optimization
Yuchen Lu, Zherui Chen, Tongyang Li
Metastability separates apparent equilibration from true convergence: a dynamical system can remain near an intermediate state long before reaching its stationary state. In quantum…
Finding Stationary Points by Comparisons
Helin Wang, Chenyi Zhang, Xiwen Tao +2
We study the problem of finding stationary points of non-convex functions when access to the objective is provided only through a comparison oracle that, given two points, outputs…
Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
Yexin Zhang, Chenyi Zhang, Cong Fang +2
Finite-sum optimization has wide applications in machine learning, covering important problems such as support vector machines, regression, etc. In this paper, we initiate the stud…
Quantum Non-Identical Mean Estimation: Efficient Algorithms and Fundamental Limits
Jiachen Hu, Tongyang Li, Xinzhao Wang +3
We systematically investigate quantum algorithms and lower bounds for mean estimation given query access to non-identically distributed samples. On the one hand, we give quantum me…
Gradient Testing and Estimation by Comparisons
Xiwen Tao, Chenyi Zhang, Helin Wang +2
We study gradient testing and gradient estimation of smooth functions using only a comparison oracle that, given two points, indicates which one has the larger function value. For…
Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss
Hao Wang, Chenyi Zhang, Tongyang Li
The problem of minimizing the maximum of convex, Lipschitz functions plays significant roles in optimization and machine learning. It has a series of results, with the most rec…
Quantum Langevin Dynamics for Optimization
Zherui Chen, Yuchen Lu, Hao Wang +2
We initiate the study of utilizing Quantum Langevin Dynamics (QLD) to solve optimization problems, particularly those non-convex objective functions that present substantial obstac…