本文汇总了NIPS、ICML、CVPR会议中量子计算与机器学习相关成果。涉及量子算法优化、量子神经网络、量子强化学习等多方面，如量子加速优化近似凸函数、量子策略梯度算法等，展示了量子计算在机器学习领域的广泛应用。
NIPS
Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex BanditsTongyang Li, Ruizhe Zhang.
Matrix Multiplicative Weights Updates in Quantum Zero-Sum Games: Conservation Laws & Recurrence Rahul Jain, Georgios Piliouras, Ryann Sim
Differentiable Analog Quantum Computing for Optimization and Control Jiaqi Leng, Yuxiang Peng, Yi-Ling Qiao, Ming Lin, Xiaodi Wu
GraphQNTK: Quantum Neural Tangent Kernel for Graph Data Yehui Tang, Junchi Yan
Systematic improvement of neural network quantum states using Lanczos Hongwei Chen, Douglas Hendry, Phillip Weinberg, Adrian Feiguin
Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits Kaining Zhang, Liu Liu, Min-Hsiu Hsieh, Dacheng Tao
Concentration of Data Encoding in Parameterized Quantum Circuits Guangxi Li, Ruilin Ye, Xuanqiang Zhao, Xin Wang
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants Andrew M. Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang
Power and limitations of single-qubit native quantum neural networks Zhan Yu, Hongshun Yao, Mujin Li, Xin Wang
The Inductive Bias of Quantum Kernels Jonas Kübler, Simon Buchholz, Bernhard Schölkopf
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