Stochastic gradient descent for hybrid quantum-classical optimization

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Stochastic gradient descent for hybrid quantum-classical optimization

2 October 2019

Johannes Jakob Meyer

Maria Schuld

Paul K. Fährmann

Barthélémy Meynard-Piganeau

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Papers citing "Stochastic gradient descent for hybrid quantum-classical optimization"

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Title
Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits Kaining Zhang Liu Liu Min-hsiu Hsieh Dacheng Tao 125 63 0 20 Feb 2025
Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits Hoang-Quan Nguyen Xuan-Bac Nguyen Samuel Yen-Chi Chen Hugh Churchill Nicholas Borys Samee U. Khan Khoa Luu DiffM 75 5 0 02 Jun 2024
Training-efficient density quantum machine learning Brian Coyle El Amine Cherrat Nishant Jain Natansh Mathur Snehal Raj Skander Kazdaghli Iordanis Kerenidis 101 5 0 30 May 2024
Stochastic noise can be helpful for variational quantum algorithms Junyu Liu Frederik Wilde A. A. Mele Liang Jiang Jens Eisert Jens Eisert 61 34 0 13 Oct 2022
Noise-Resilient Variational Hybrid Quantum-Classical Optimization Laura Gentini A. Cuccoli S. Pirandola P. Verrucchi L. Banchi 51 26 0 13 Dec 2019
Parameterized quantum circuits as machine learning models Marcello Benedetti Erika Lloyd Stefan H. Sack Mattia Fiorentini 107 895 0 18 Jun 2019
Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD Phuong Ha Nguyen Lam M. Nguyen Marten van Dijk LRM 50 31 0 10 Oct 2018
Stochastic Gradient Descent with Biased but Consistent Gradient Estimators Jie Chen Ronny Luss 79 45 0 31 Jul 2018
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes Xiaoyun Li Francesco Orabona 69 298 0 21 May 2018
Supervised learning with quantum enhanced feature spaces Vojtěch Havlíček A. Córcoles K. Temme A. Harrow A. Kandala J. Chow J. Gambetta 84 1,833 0 30 Apr 2018
An Alternative View: When Does SGD Escape Local Minima? Robert D. Kleinberg Yuanzhi Li Yang Yuan MLT 77 317 0 17 Feb 2018
Don't Decay the Learning Rate, Increase the Batch Size Samuel L. Smith Pieter-Jan Kindermans Chris Ying Quoc V. Le ODL 107 996 0 01 Nov 2017
An overview of gradient descent optimization algorithms Sebastian Ruder ODL 206 6,203 0 15 Sep 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark Schmidt 280 1,221 0 16 Aug 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Scalable Kernel Methods via Doubly Stochastic Gradients Bo Dai Bo Xie Niao He Yingyu Liang Anant Raj Maria-Florina Balcan Le Song 150 230 0 21 Jul 2014
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu Benjamin Recht Christopher Ré Stephen J. Wright 201 2,273 0 28 Jun 2011