no code implementations • 1 Jan 2021 • Samuel A. Stein, Ray Marie Tischio, Betis Baheri, YiWen Chen, Ying Mao, Qiang Guan, Ang Li, Bo Fang
In this paper, we propose GenQu, a hybrid and general-purpose quantum framework for learning classical data through quantum states.
no code implementations • 16 Oct 2020 • Daniel Chen, Yekun Xu, Betis Baheri, Chuan Bi, Ying Mao, Qiang Quan, Shuai Xu
In this work, we developed an algorithm for principal component regression that runs in time polylogarithmic to the number of data points, an exponential speed up over the state-of-the-art algorithm, under the mild assumption that the input is given in some data structure that supports a norm-based sampling procedure.