Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints

27 December 2024

Papers citing "Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints"

19 / 19 papers shown

Title
DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule Maor Ivgi Oliver Hinder Y. Carmon ODL 117 66 0 08 Feb 2023
Stochastic Polyak Stepsize with a Moving Target Robert Mansel Gower Aaron Defazio Michael G. Rabbat 73 17 0 22 Jun 2021
Adam $^+$ : A Stochastic Method with Adaptive Variance Reduction Mingrui Liu Wei Zhang Francesco Orabona Tianbao Yang 48 28 0 24 Nov 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 684 41,563 0 22 Oct 2020
Better Parameter-free Stochastic Optimization with ODE Updates for Coin-Betting K. Chen John Langford Francesco Orabona 59 22 0 12 Jun 2020
A new regret analysis for Adam-type algorithms Ahmet Alacaoglu Yura Malitsky P. Mertikopoulos Volkan Cevher ODL 79 43 0 21 Mar 2020
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence Nicolas Loizou Sharan Vaswani I. Laradji Simon Lacoste-Julien 88 188 0 24 Feb 2020
On the Variance of the Adaptive Learning Rate and Beyond Liyuan Liu Haoming Jiang Pengcheng He Weizhu Chen Xiaodong Liu Jianfeng Gao Jiawei Han ODL 298 1,909 0 08 Aug 2019
Momentum-Based Variance Reduction in Non-Convex SGD Ashok Cutkosky Francesco Orabona ODL 96 410 0 24 May 2019
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates Sharan Vaswani Aaron Mishkin I. Laradji Mark Schmidt Gauthier Gidel Simon Lacoste-Julien ODL 111 210 0 24 May 2019
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization Dongruo Zhou Yiqi Tang Yuan Cao Ziyan Yang Quanquan Gu 83 150 0 16 Aug 2018
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks Jinghui Chen Dongruo Zhou Yiqi Tang Ziyan Yang Yuan Cao Quanquan Gu ODL 101 193 0 18 Jun 2018
Large Batch Training of Convolutional Networks Yang You Igor Gitman Boris Ginsburg ODL 154 852 0 13 Aug 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 859 36,910 0 25 Aug 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 362 8,005 0 23 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,641 0 10 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,433 0 22 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,575 0 04 Sep 2014
Less Regret via Online Conditioning Matthew J. Streeter H. B. McMahan ODL 101 66 0 25 Feb 2010