Optimization · Stochastic Optimization

TitleAuthors
Double Quantization for Communication-Efficient Distributed OptimizationYue Yu · Jiaxiang Wu · Longbo Huang
Optimal Decision Tree with Noisy OutcomesSu Jia · viswanath nagarajan · Fatemeh Navidi · R Ravi
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-UpDominic Richards · Patrick Rebeschini
RSN: Randomized Subspace NewtonRobert Gower · Dmitry Koralev · Felix Lieder · Peter Richtarik
Towards closing the gap between the theory and practice of SVRGOthmane Sebbouh · Nidham Gazagnadou · Samy Jelassi · Francis Bach · Robert Gower
UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained OptimizationAli Kavis · Kfir Y. Levy · Francis Bach · Volkan Cevher
A Latent Variational Framework for Stochastic OptimizationPhilippe Casgrain
A Stochastic Composite Gradient Method with Incremental Variance ReductionJunyu Zhang · Lin Xiao
A Universally Optimal Multistage Accelerated Stochastic Gradient MethodNecdet Serhat Aybat · Alireza Fallah · Mert Gurbuzbalaban · Asuman Ozdaglar
On the convergence of single-call stochastic extra-gradient methodsYu-Guan Hsieh · Franck Iutzeler · Jérôme Malick · Panayotis Mertikopoulos
On the Ineffectiveness of Variance Reduced Optimization for Deep LearningAaron Defazio · Leon Bottou
Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRGYujia Jin · Aaron Sidford
Understanding the Role of Momentum in Stochastic Gradient MethodsIgor Gitman · Hunter Lang · Pengchuan Zhang · Lin Xiao
Alleviating Label Switching with Optimal TransportPierre Monteiller · Sebastian Claici · Edward Chien · Farzaneh Mirzazadeh · Justin M Solomon · Mikhail Yurochkin
Beating SGD Saturation with Tail-Averaging and MinibatchingNicole Muecke · Gergely Neu · Lorenzo Rosasco
Continuous-time Models for Stochastic Optimization AlgorithmsAntonio Orvieto · Aurelien Lucchi
Distributed estimation of the inverse Hessian by determinantal averagingMichal Derezinski · Michael W Mahoney
The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least SquaresRong Ge · Sham Kakade · Rahul Kidambi · Praneeth Netrapalli
Think out of the "Box": Generically-Constrained Asynchronous Composite Optimization and HedgingPooria Joulani · András György · Csaba Szepesvari
Variance Reduction for Matrix GamesYair Carmon · Yujia Jin · Aaron Sidford · Kevin Tian