Stochastic Zeroth Order Gradient and Hessian Estimators: Variance
Reduction and Refined Bias Bounds

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Stochastic Zeroth Order Gradient and Hessian Estimators: Variance Reduction and Refined Bias Bounds

29 May 2022

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Papers citing "Stochastic Zeroth Order Gradient and Hessian Estimators: Variance Reduction and Refined Bias Bounds"

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Title
A Structured Tour of Optimization with Finite Differences Marco Rando C. Molinari Lorenzo Rosasco S. Villa 160 0 0 26 May 2025
From the Greene--Wu Convolution to Gradient Estimation over Riemannian Manifolds Tianyu Wang Yifeng Huang Didong Li 40 8 0 17 Aug 2021
A One-bit, Comparison-Based Gradient Estimator HanQin Cai Daniel McKenzie W. Yin Zhenliang Zhang 90 17 0 06 Oct 2020
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning Sijia Liu Pin-Yu Chen B. Kailkhura Gaoyuan Zhang A. Hero III P. Varshney 72 232 0 11 Jun 2020
Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling HanQin Cai Daniel McKenzie W. Yin Zhenliang Zhang 115 50 0 29 Mar 2020
Optimal rates for zero-order convex optimization: the power of two function evaluations John C. Duchi Michael I. Jordan Martin J. Wainwright Andre Wibisono 79 489 0 07 Dec 2013
Query Complexity of Derivative-Free Optimization Kevin Jamieson Robert D. Nowak Benjamin Recht 170 160 0 11 Sep 2012
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization Ohad Shamir 417 193 0 11 Sep 2012
Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach Y. Plan Roman Vershynin 242 457 0 06 Feb 2012