Quantum Machine Learning
521 papers for year 2024
Quantum Machine Learning Research Context
This category covers quantum machine learning research, including quantum kernels, variational classifiers, hybrid learning systems, generative models, and QML benchmarks.
Showing 313-324 of 521
Quadratic Advantage with Quantum Randomized Smoothing Applied to Time-Series Analysis
Nicola Franco, Marie Kempkes, Jakob Spiegelberg, Jeanette Miriam Lorenz
QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation
Zhuo Chen, Rumen Dangovski, Charlotte Loh, Owen Dugan, Di Luo, Marin Soljačić
Quantifying entanglement for unknown quantum states via artificial neural networks.
Pan GZ, Yang M, Zhou J, Yuan H, Miao C, Zhang G.
Quantum Active Learning
Yongcheng Ding, Yue Ban, Mikel Sanz, José D. Martín-Guerrero, Xi Chen
Quantum Advantage with Faulty Oracle
David Rasmussen Lolck, Laura Mančinska, Manaswi Paraashar
Quantum Algorithm for a Stochastic Multicloud Model
Kazumasa Ueno, Hiroaki Miura
Quantum Algorithm for Online Exp-concave Optimization
Jianhao He, Chengchang Liu, Xutong Liu, Lvzhou Li, John C. S. Lui
Quantum Algorithm for Sparse Online Learning with Truncated Gradient Descent
Debbie Lim, Yixian Qiu, Patrick Rebentrost, Qisheng Wang
Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
Yexin Zhang, Chenyi Zhang, Cong Fang, Liwei Wang, Tongyang Li
Quantum algorithms for optimizers
Giacomo Nannicini
Quantum Algorithms for Realizing Symmetric, Asymmetric, and Antisymmetric Projectors
Margarite L. LaBorde, Soorya Rethinasamy, Mark M. Wilde
Quantum annealing for nearest neighbour compliance problem.
Müller S, Phillipson F.