Towards provably efficient quantum algorithms for large-scale machine-learning models

no code implementations • 6 Mar 2023 • Junyu Liu, Minzhao Liu, Jin-Peng Liu, Ziyu Ye, Yunfei Wang, Yuri Alexeev, Jens Eisert, Liang Jiang

Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-training and fine-tuning process.

Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants

no code implementations • 12 Oct 2022 • Andrew M. Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang

We also prove a $1/\epsilon^{1-o(1)}$ quantum lower bound for estimating normalizing constants, implying near-optimality of our quantum algorithms in $\epsilon$.