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Fast Randomized Kernel Methods With Statistical Guarantees

2 November 2014

Papers citing "Fast Randomized Kernel Methods With Statistical Guarantees"

37 / 37 papers shown

Title
Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning Wanyun Xie F. Tonin Volkan Cevher 32 0 0 30 May 2025
Supervised Kernel Thinning Albert Gong Kyuseong Choi Raaz Dwivedi 177 0 0 17 Oct 2024
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning Michal Dereziñski Christopher Musco Jiaming Yang 121 2 0 09 May 2024
Mean Parity Fair Regression in RKHS Shaokui Wei Jiayin Liu Bing Li H. Zha 48 3 0 21 Feb 2023
A Distribution Free Truncated Kernel Ridge Regression Estimator and Related Spectral Analyses Asma Ben Saber Abderrazek Karoui 45 1 0 17 Jan 2023
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning Sattar Vakili Jonathan Scarlett Da-shan Shiu A. Bernacchia 88 19 0 08 Feb 2022
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression Giacomo Meanti Luigi Carratino Ernesto De Vito Lorenzo Rosasco 61 13 0 17 Jan 2022
Nearly Optimal Algorithms for Level Set Estimation Blake Mason Romain Camilleri Subhojyoti Mukherjee Kevin Jamieson Robert D. Nowak Lalit P. Jain 77 23 0 02 Nov 2021
Knowledge-Adaptation Priors Mohammad Emtiyaz Khan S. Swaroop BDL VLM ODL 53 27 0 16 Jun 2021
High-Dimensional Experimental Design and Kernel Bandits Romain Camilleri Julian Katz-Samuels Kevin Jamieson 83 57 0 12 May 2021
Near-linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification Daniele Calandriello Luigi Carratino A. Lazaric Michal Valko Lorenzo Rosasco 81 19 0 23 Feb 2020
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness George Wynne F. Briol Mark Girolami 85 56 0 29 Jan 2020
Large-scale Kernel Methods and Applications to Lifelong Robot Learning Raffaello Camoriano 82 1 0 11 Dec 2019
Exact expressions for double descent and implicit regularization via surrogate random design Michal Derezinski Feynman T. Liang Michael W. Mahoney 82 78 0 10 Dec 2019
Statistical and Computational Trade-Offs in Kernel K-Means Daniele Calandriello Lorenzo Rosasco 51 32 0 27 Aug 2019
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$ -means Clustering Manuel Fernández David P. Woodruff T. Yasuda 60 7 0 15 May 2019
Spatial Analysis Made Easy with Linear Regression and Kernels Philip Milton E. Giorgi Samir Bhatt 55 20 0 22 Feb 2019
Kernel Conjugate Gradient Methods with Random Projections Bailey Kacsmar Douglas R Stinson 54 4 0 05 Nov 2018
On Fast Leverage Score Sampling and Optimal Learning Alessandro Rudi Daniele Calandriello Luigi Carratino Lorenzo Rosasco 83 82 0 31 Oct 2018
Data-dependent compression of random features for large-scale kernel approximation Raj Agrawal Trevor Campbell Jonathan H. Huggins Tamara Broderick 48 20 0 09 Oct 2018
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees Jonathan H. Huggins Trevor Campbell Mikolaj Kasprzak Tamara Broderick 89 15 0 26 Jun 2018
A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression E. Rebrova Gustavo Chavez Yang Liu P. Ghysels Xin Li 55 22 0 27 Mar 2018
Distributed Adaptive Sampling for Kernel Matrix Approximation Daniele Calandriello A. Lazaric Michal Valko 130 24 0 27 Mar 2018
Second-Order Kernel Online Convex Optimization with Adaptive Sketching Daniele Calandriello A. Lazaric Michal Valko 72 40 0 15 Jun 2017
Randomized Clustered Nystrom for Large-Scale Kernel Machines Farhad Pourkamali Anaraki Stephen Becker 80 33 0 20 Dec 2016
Sharper Bounds for Regularized Data Fitting H. Avron K. Clarkson David P. Woodruff 85 58 0 10 Nov 2016
Fast DPP Sampling for Nyström with Application to Kernel Methods Chengtao Li Stefanie Jegelka S. Sra 87 76 0 19 Mar 2016
Large Scale Kernel Learning using Block Coordinate Descent Stephen Tu Rebecca Roelofs Shivaram Venkataraman Benjamin Recht 80 43 0 17 Feb 2016
Generalization Properties of Learning with Random Features Alessandro Rudi Lorenzo Rosasco MLT 102 331 0 14 Feb 2016
Input Sparsity Time Low-Rank Approximation via Ridge Leverage Score Sampling Michael B. Cohen Cameron Musco Christopher Musco 83 144 0 23 Nov 2015
NYTRO: When Subsampling Meets Early Stopping Tomás Angles Raffaello Camoriano Alessandro Rudi Lorenzo Rosasco 92 32 0 19 Oct 2015
Less is More: Nyström Computational Regularization Alessandro Rudi Raffaello Camoriano Lorenzo Rosasco 97 277 0 16 Jul 2015
Optimal Rates for Random Fourier Features Bharath K. Sriperumbudur Z. Szabó 108 130 0 06 Jun 2015
Randomized sketches for kernels: Fast and optimal non-parametric regression Yun Yang Mert Pilanci Martin J. Wainwright 103 174 0 25 Jan 2015
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels H. Avron Vikas Sindhwani Jiyan Yang Michael W. Mahoney 97 166 0 29 Dec 2014
The Statistics of Streaming Sparse Regression Jacob Steinhardt Stefan Wager Percy Liang 266 10 0 13 Dec 2014
On the Complexity of Learning with Kernels Nicolò Cesa-Bianchi Yishay Mansour Ohad Shamir 94 38 0 05 Nov 2014