Randomized sketches for kernels: Fast and optimal non-parametric regression

25 January 2015

Papers citing "Randomized sketches for kernels: Fast and optimal non-parametric regression"

50 / 64 papers shown

Title
Deep Sketched Output Kernel Regression for Structured Prediction T. Ahmad Junjie Yang Pierre Laforgue Florence dÁlché-Buc UQCV 85 1 0 13 Jun 2024
A Bound on the Maximal Marginal Degrees of Freedom Paul Dommel 191 1 0 20 Feb 2024
Spectral Regularized Kernel Goodness-of-Fit Tests Omar Hagrass Bharath K. Sriperumbudur Bing Li 143 4 0 08 Aug 2023
Noisy recovery from random linear observations: Sharp minimax rates under elliptical constraints Reese Pathak Martin J. Wainwright Lin Xiao 58 5 0 22 Mar 2023
A Distribution Free Truncated Kernel Ridge Regression Estimator and Related Spectral Analyses Asma Ben Saber Abderrazek Karoui 47 1 0 17 Jan 2023
Spectral Regularized Kernel Two-Sample Tests Omar Hagrass Bharath K. Sriperumbudur Bing Li 75 15 0 19 Dec 2022
Regularized Stein Variational Gradient Flow Ye He Krishnakumar Balasubramanian Bharath K. Sriperumbudur Jianfeng Lu OT 65 12 0 15 Nov 2022
Generalized Kernel Regularized Least Squares Qing Chang Max Goplerud 51 5 0 28 Sep 2022
Target alignment in truncated kernel ridge regression Arash A. Amini R. Baumgartner Dai Feng 51 3 0 28 Jun 2022
Sampling with replacement vs Poisson sampling: a comparative study in optimal subsampling Jing Wang Jiahui Zou Haiying Wang 78 18 0 17 May 2022
Optimally tackling covariate shift in RKHS-based nonparametric regression Cong Ma Reese Pathak Martin J. Wainwright 64 45 0 06 May 2022
Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences Yifan Chen Qi Zeng Dilek Z. Hakkani-Tür Di Jin Heng Ji Yun Yang 83 5 0 10 Dec 2021
Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches Shaogao Lv Xin He Junhui Wang 67 1 0 18 Oct 2021
Optimal policy evaluation using kernel-based temporal difference methods Yaqi Duan Mengdi Wang Martin J. Wainwright OffRL 66 27 0 24 Sep 2021
Functional Principal Subspace Sampling for Large Scale Functional Data Analysis Shiyuan He Xiaomeng Yan 112 4 0 08 Sep 2021
Statistical Optimality and Computational Efficiency of Nyström Kernel PCA Nicholas Sterge Bharath K. Sriperumbudur 140 10 0 19 May 2021
Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality Jonathan Lacotte Yifei Wang Mert Pilanci 67 17 0 15 May 2021
An Efficient One-Class SVM for Anomaly Detection in the Internet of Things Kun Yang Samory Kpotufe Nick Feamster 39 37 0 22 Apr 2021
Fast Statistical Leverage Score Approximation in Kernel Ridge Regression Yifan Chen Yun Yang 66 16 0 09 Mar 2021
Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional Optimization: Sharp Analysis and Lower Bounds Jonathan Lacotte Mert Pilanci 112 12 0 13 Dec 2020
On the coercivity condition in the learning of interacting particle systems Zhongyan Li Fei Lu 72 4 0 20 Nov 2020
A Survey on Large-scale Machine Learning Meng Wang Weijie Fu Xiangnan He Shijie Hao Xindong Wu 84 112 0 10 Aug 2020
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization Michal Derezinski Burak Bartan Mert Pilanci Michael W. Mahoney 59 27 0 02 Jul 2020
Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck Alec Koppel Hrusikesha Pradhan K. Rajawat 44 32 0 23 Apr 2020
Optimal Randomized First-Order Methods for Least-Squares Problems Jonathan Lacotte Mert Pilanci 91 30 0 21 Feb 2020
Optimal Iterative Sketching with the Subsampled Randomized Hadamard Transform Jonathan Lacotte Sifan Liu Yan Sun Mert Pilanci 76 8 0 03 Feb 2020
Sub-Gaussian Matrices on Sets: Optimal Tail Dependence and Applications Halyun Jeong Xiaowei Li Y. Plan Özgür Yilmaz 70 18 0 28 Jan 2020
Statistical Limits of Supervised Quantum Learning C. Ciliberto Andrea Rocchetto Alessandro Rudi Leonard Wossnig 58 4 0 28 Jan 2020
Adaptive Stopping Rule for Kernel-based Gradient Descent Algorithms Xiangyu Chang Shao-Bo Lin 46 0 0 09 Jan 2020
Low Rank Approximation for Smoothing Spline via Eigensystem Truncation Danqing Xu Yuedong Wang 23 2 0 23 Nov 2019
Concentration of kernel matrices with application to kernel spectral clustering Arash A. Amini Zahra S. Razaee 49 14 0 07 Sep 2019
Distributed Black-Box Optimization via Error Correcting Codes Burak Bartan Mert Pilanci 124 2 0 13 Jul 2019
Don't take it lightly: Phasing optical random projections with unknown operators Sidharth Gupta Rémi Gribonval L. Daudet Ivan Dokmanić 36 10 0 03 Jul 2019
High-Dimensional Optimization in Adaptive Random Subspaces Jonathan Lacotte Mert Pilanci Marco Pavone 63 16 0 27 Jun 2019
Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data Daniel Zilber Matthias Katzfuss 84 34 0 18 Jun 2019
Spectrally-truncated kernel ridge regression and its free lunch Arash A. Amini 52 6 0 14 Jun 2019
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound Lin F. Yang Mengdi Wang OffRL GP 119 288 0 24 May 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
An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation Jonathan Scarlett Volkan Cevher 114 41 0 02 Jan 2019
Convex Relaxations of Convolutional Neural Nets Burak Bartan Mert Pilanci 103 5 0 31 Dec 2018
OverSketch: Approximate Matrix Multiplication for the Cloud Vipul Gupta Ryan Sherman Thomas Courtade Kannan Ramchandran 62 50 0 06 Nov 2018
Kernel Conjugate Gradient Methods with Random Projections Bailey Kacsmar Douglas R Stinson 54 4 0 05 Nov 2018
Asymptotics for Sketching in Least Squares Regression Yan Sun Sifan Liu 61 13 0 14 Oct 2018
Data-dependent compression of random features for large-scale kernel approximation Raj Agrawal Trevor Campbell Jonathan H. Huggins Tamara Broderick 51 20 0 09 Oct 2018
$Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features$ Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features Enayat Ullah Poorya Mianjy T. V. Marinov R. Arora 129 22 0 02 Aug 2018
Matrix completion and extrapolation via kernel regression Pere Giménez-Febrer A. Pagés-Zamora G. Giannakis 44 13 0 01 Aug 2018
Learning with SGD and Random Features Luigi Carratino Alessandro Rudi Lorenzo Rosasco 83 78 0 17 Jul 2018
How Many Machines Can We Use in Parallel Computing for Kernel Ridge Regression? Meimei Liu Zuofeng Shang Guang Cheng 52 8 0 25 May 2018
Sketching the order of events Terry Lyons Harald Oberhauser 43 5 0 31 Aug 2017
Frequentist coverage and sup-norm convergence rate in Gaussian process regression Yun Yang A. Bhattacharya D. Pati 78 54 0 16 Aug 2017