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

6 March 2023

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

22 / 22 papers shown

Title
Q-Newton: Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent Pingzhi Li Junyu Liu Hanrui Wang Tianlong Chen 137 2 0 30 Apr 2024
A super-polynomial quantum-classical separation for density modelling Niklas Pirnay R. Sweke Jens Eisert Jean-Pierre Seifert 26 15 0 26 Oct 2022
Stochastic noise can be helpful for variational quantum algorithms Junyu Liu Frederik Wilde A. A. Mele Liang Jiang Jens Eisert Jens Eisert 50 34 0 13 Oct 2022
Solving Quantitative Reasoning Problems with Language Models Aitor Lewkowycz Anders Andreassen David Dohan Ethan Dyer Henryk Michalewski ... Theo Gutman-Solo Yuhuai Wu Behnam Neyshabur Guy Gur-Ari Vedant Misra ReLM ELM LRM 142 831 0 29 Jun 2022
PaLM: Scaling Language Modeling with Pathways Aakanksha Chowdhery Sharan Narang Jacob Devlin Maarten Bosma Gaurav Mishra ... Kathy Meier-Hellstern Douglas Eck J. Dean Slav Petrov Noah Fiedel PILM LRM 441 6,222 0 05 Apr 2022
Quantum advantage in learning from experiments Hsin-Yuan Huang Michael Broughton Jordan S. Cotler Sitan Chen Jingkai Li ... Hartmut Neven Ryan Babbush R. Kueng J. Preskill Jarrod R. McClean 41 476 0 01 Dec 2021
The Principles of Deep Learning Theory Daniel A. Roberts Sho Yaida Boris Hanin FaML PINN GNN 59 245 0 18 Jun 2021
Carbon Emissions and Large Neural Network Training David A. Patterson Joseph E. Gonzalez Quoc V. Le Chen Liang Lluís-Miquel Munguía D. Rothchild David R. So Maud Texier J. Dean AI4CE 331 667 0 21 Apr 2021
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning Roberto Bondesan Max Welling 63 7 0 08 Mar 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 305 717 0 31 Jan 2021
Information-theoretic bounds on quantum advantage in machine learning Hsin-Yuan Huang R. Kueng J. Preskill 89 220 0 07 Jan 2021
Variational Quantum Algorithms M. Cerezo A. Arrasmith Ryan Babbush S. Benjamin Suguru Endo ... Jarrod R. McClean K. Mitarai Xiao Yuan L. Cincio Patrick J. Coles 86 2,518 0 16 Dec 2020
Power of data in quantum machine learning Hsin-Yuan Huang Michael Broughton Masoud Mohseni Ryan Babbush Sergio Boixo Hartmut Neven Jarrod R. McClean 69 645 0 03 Nov 2020
A rigorous and robust quantum speed-up in supervised machine learning Yunchao Liu Srinivasan Arunachalam K. Temme 72 542 0 05 Oct 2020
On the Quantum versus Classical Learnability of Discrete Distributions R. Sweke Jean-Pierre Seifert D. Hangleiter Jens Eisert 51 93 0 28 Jul 2020
Predicting Many Properties of a Quantum System from Very Few Measurements Hsin-Yuan Huang R. Kueng J. Preskill 43 1,100 0 18 Feb 2020
Quantum principal component analysis only achieves an exponential speedup because of its state preparation assumptions Ewin Tang 49 109 0 31 Oct 2018
SNIP: Single-shot Network Pruning based on Connection Sensitivity Namhoon Lee Thalaiyasingam Ajanthan Philip Torr VLM 249 1,198 0 04 Oct 2018
Supervised learning with quantum enhanced feature spaces Vojtěch Havlíček A. Córcoles K. Temme A. Harrow A. Kandala J. Chow J. Gambetta 66 1,823 0 30 Apr 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 225 3,461 0 09 Mar 2018
Quantum Machine Learning Jacob Biamonte P. Wittek Nicola Pancotti Patrick Rebentrost N. Wiebe S. Lloyd 50 2,014 0 28 Nov 2016
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 307 18,609 0 06 Feb 2015