HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation

13 February 2018

Papers citing "HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation"

5 / 5 papers shown

Title
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 79 50 0 14 Jun 2020
Statistical Inference for Model Parameters in Stochastic Gradient Descent Xi Chen Jason D. Lee Xin T. Tong Yichen Zhang 51 138 0 27 Oct 2016
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 112 1,817 0 01 Jul 2014
Degrees of freedom in lasso problems Robert Tibshirani Jonathan E. Taylor 100 363 0 02 Nov 2011
Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization Alekh Agarwal Peter L. Bartlett Pradeep Ravikumar Martin J. Wainwright 155 248 0 03 Sep 2010