A Smoother Way to Train Structured Prediction Models

8 February 2019

Papers citing "A Smoother Way to Train Structured Prediction Models"

8 / 8 papers shown

Title
Modified Gauss-Newton Algorithms under Noise Krishna Pillutla Vincent Roulet Sham Kakade Zaïd Harchaoui 29 3 0 18 May 2023
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters Luc Brogat-Motte Rémi Flamary Céline Brouard Juho Rousu Florence dÁlché-Buc 38 19 0 08 Feb 2022
FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients Jaemin Shin Yuanchun Li Yunxin Liu Sung-Ju Lee FedML 19 74 0 05 Jan 2022
Scaling Structured Inference with Randomization Yao Fu John P. Cunningham Mirella Lapata BDL 32 2 0 07 Dec 2021
Learning with Differentiable Perturbed Optimizers Quentin Berthet Mathieu Blondel O. Teboul Marco Cuturi Jean-Philippe Vert Francis R. Bach 29 106 0 20 Feb 2020
RNA Secondary Structure Prediction By Learning Unrolled Algorithms Xinshi Chen Yu Li Ramzan Umarov Xin Gao Le Song SyDa AI4TS 27 118 0 13 Feb 2020
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 79 317 0 18 Feb 2014
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark Schmidt Francis R. Bach 128 259 0 10 Dec 2012