Scalable Kernel Methods via Doubly Stochastic Gradients

21 July 2014

Papers citing "Scalable Kernel Methods via Doubly Stochastic Gradients"

34 / 34 papers shown

Title
Demystifying SGD with Doubly Stochastic Gradients Kyurae Kim Joohwan Ko Yian Ma Jacob R. Gardner 53 0 0 03 Jun 2024
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding Tongzheng Ren Zhaolin Ren Haitong Ma Na Li Bo Dai 30 10 0 08 Apr 2023
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan Kelly Semyon Malamud 16 0 0 26 Jan 2023
QC-ODKLA: Quantized and Communication-Censored Online Decentralized Kernel Learning via Linearized ADMM Ping Xu Yue Wang Xiang Chen Zhi Tian 21 2 0 04 Aug 2022
A Sparse Expansion For Deep Gaussian Processes Liang Ding Rui Tuo Shahin Shahrampour 16 6 0 11 Dec 2021
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning Tongzheng Ren Tianjun Zhang Csaba Szepesvári Bo Dai 24 19 0 22 Nov 2021
Spectral risk-based learning using unbounded losses Matthew J. Holland El Mehdi Haress 19 10 0 11 May 2021
Action Recognition with Kernel-based Graph Convolutional Networks H. Sahbi GNN 23 1 0 28 Dec 2020
Kernel methods through the roof: handling billions of points efficiently Giacomo Meanti Luigi Carratino Lorenzo Rosasco Alessandro Rudi 19 112 0 18 Jun 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 44 172 0 23 Apr 2020
COKE: Communication-Censored Decentralized Kernel Learning Ping Xu Yue Wang Xiang Chen Z. Tian 15 20 0 28 Jan 2020
Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization Wanli Shi Bin Gu Xinag Li Heng-Chiao Huang 29 13 0 24 Dec 2019
Stochastic gradient descent for hybrid quantum-classical optimization R. Sweke Frederik Wilde Johannes Jakob Meyer Maria Schuld Paul K. Fährmann Barthélémy Meynard-Piganeau Jens Eisert 17 236 0 02 Oct 2019
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization Wanli Shi Bin Gu Xiang Li Xiang Geng Heng-Chiao Huang 26 15 0 29 Jul 2019
No Training Required: Exploring Random Encoders for Sentence Classification John Wieting Douwe Kiela 8 98 0 29 Jan 2019
On Kernel Derivative Approximation with Random Fourier Features Z. Szabó Bharath K. Sriperumbudur 29 12 0 11 Oct 2018
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation Bo Dai Albert Eaton Shaw Lihong Li Lin Xiao Niao He Zhen Liu Jianshu Chen Le Song 26 25 0 29 Dec 2017
Boosting the Actor with Dual Critic Bo Dai Albert Eaton Shaw Niao He Lihong Li Le Song 29 46 0 29 Dec 2017
Deep Expander Networks: Efficient Deep Networks from Graph Theory Ameya Prabhu G. Varma A. Namboodiri GNN 30 70 0 23 Nov 2017
Decentralized Online Learning with Kernels Alec Koppel Santiago Paternain C. Richard Alejandro Ribeiro 18 51 0 11 Oct 2017
Diving into the shallows: a computational perspective on large-scale shallow learning Siyuan Ma M. Belkin 24 75 0 30 Mar 2017
Deep Kernelized Autoencoders Michael C. Kampffmeyer Sigurd Løkse F. Bianchi Robert Jenssen L. Livi 20 18 0 08 Feb 2017
Parsimonious Online Learning with Kernels via Sparse Projections in Function Space Alec Koppel Garrett A. Warnell Ethan Stump Alejandro Ribeiro 18 79 0 13 Dec 2016
Faster Kernel Ridge Regression Using Sketching and Preconditioning H. Avron K. Clarkson David P. Woodruff 35 121 0 10 Nov 2016
Theory of the GMM Kernel Ping Li Cun-Hui Zhang 30 23 0 01 Aug 2016
Learning from Conditional Distributions via Dual Embeddings Bo Dai Niao He Yunpeng Pan Byron Boots Le Song 35 21 0 15 Jul 2016
The Mondrian Kernel Matej Balog Balaji Lakshminarayanan Zoubin Ghahramani Daniel M. Roy Yee Whye Teh 16 26 0 16 Jun 2016
Linearized GMM Kernels and Normalized Random Fourier Features Ping Li 24 9 0 18 May 2016
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA Kirthevasan Kandasamy Yaoliang Yu 20 44 0 31 Jan 2016
NYTRO: When Subsampling Meets Early Stopping Tomás Angles Raffaello Camoriano Alessandro Rudi Lorenzo Rosasco 32 32 0 19 Oct 2015
Scan $B$ -Statistic for Kernel Change-Point Detection Shuang Li Yao Xie H. Dai Le Song 43 106 0 05 Jul 2015
On the Error of Random Fourier Features Danica J. Sutherland J. Schneider 30 189 0 09 Jun 2015
A Practical Guide to Randomized Matrix Computations with MATLAB Implementations Shusen Wang 24 37 0 28 May 2015
Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages Wittawat Jitkrittum A. Gretton N. Heess S. M. Ali Eslami Balaji Lakshminarayanan Dino Sejdinovic Z. Szabó 32 33 0 09 Mar 2015