Constrained Empirical Risk Minimization: Theory and Practice

Constrained Empirical Risk Minimization: Theory and Practice

9 February 2023

Ray Sheombarsing

Jan-Jakob Sonke

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Papers citing "Constrained Empirical Risk Minimization: Theory and Practice"

19 / 19 papers shown

Title
POLICE: Provably Optimal Linear Constraint Enforcement for Deep Neural Networks Randall Balestriero Yann LeCun 75 17 0 02 Nov 2022
Neural Conservation Laws: A Divergence-Free Perspective Jack Richter-Powell Y. Lipman Ricky T. Q. Chen 103 56 0 04 Oct 2022
Better Training using Weight-Constrained Stochastic Dynamics Benedict Leimkuhler Tiffany J. Vlaar Timothée Pouchon Amos Storkey 40 9 0 20 Jun 2021
Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds Maurice Weiler Patrick Forré E. Verlinde Max Welling 57 84 0 10 Jun 2021
The Medical Segmentation Decathlon Michela Antonelli Annika Reinke Spyridon Bakas Keyvan Farahani AnnetteKopp-Schneider ... Zhanwei Xu Yefeng Zheng Amber L. Simpson Lena Maier-Hein M. Jorge Cardoso OOD 112 988 0 10 Jun 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 360 1,160 0 27 Apr 2021
DC3: A learning method for optimization with hard constraints P. Donti David Rolnick J. Zico Kolter AI4CE 71 196 0 25 Apr 2021
Constraint-Based Regularization of Neural Networks Benedict Leimkuhler Timothée Pouchon Tiffany J. Vlaar Amos Storkey 30 10 0 17 Jun 2020
Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks Wei Hu Lechao Xiao Jeffrey Pennington 64 115 0 16 Jan 2020
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes Yang You Jing Li Sashank J. Reddi Jonathan Hseu Sanjiv Kumar Srinadh Bhojanapalli Xiaodan Song J. Demmel Kurt Keutzer Cho-Jui Hsieh ODL 261 999 0 01 Apr 2019
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 162 4,444 0 16 Feb 2018
Decoupled Weight Decay Regularization I. Loshchilov Frank Hutter OffRL 151 2,151 0 14 Nov 2017
Imposing Hard Constraints on Deep Networks: Promises and Limitations Pablo Márquez-Neila Mathieu Salzmann Pascal Fua PINN UQCV 145 140 0 07 Jun 2017
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 813 3,293 0 24 Nov 2016
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 280 624 0 22 Sep 2016
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds Hongyi Zhang Sashank J. Reddi S. Sra 102 241 0 23 May 2016
Constrained Convolutional Neural Networks for Weakly Supervised Segmentation Deepak Pathak Philipp Krahenbuhl Trevor Darrell SSeg 99 614 0 11 Jun 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014
Stochastic gradient descent on Riemannian manifolds Silvere Bonnabel 117 593 0 22 Nov 2011

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