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Generalization Properties of Learning with Random Features

Generalization Properties of Learning with Random Features

14 February 2016
Alessandro Rudi
Lorenzo Rosasco
    MLT
ArXivPDFHTML

Papers citing "Generalization Properties of Learning with Random Features"

14 / 64 papers shown
Title
Reconciling modern machine learning practice and the bias-variance
  trade-off
Reconciling modern machine learning practice and the bias-variance trade-off
M. Belkin
Daniel J. Hsu
Siyuan Ma
Soumik Mandal
36
1,610
0
28 Dec 2018
On Kernel Derivative Approximation with Random Fourier Features
On Kernel Derivative Approximation with Random Fourier Features
Z. Szabó
Bharath K. Sriperumbudur
26
12
0
11 Oct 2018
Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features
Streaming Kernel PCA with O~(n)\tilde{O}(\sqrt{n})O~(n​) Random Features
Enayat Ullah
Poorya Mianjy
T. V. Marinov
R. Arora
25
20
0
02 Aug 2018
Manifold Structured Prediction
Manifold Structured Prediction
Alessandro Rudi
C. Ciliberto
Gian Maria Marconi
Lorenzo Rosasco
20
18
0
26 Jun 2018
Differential Properties of Sinkhorn Approximation for Learning with
  Wasserstein Distance
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance
Giulia Luise
Alessandro Rudi
Massimiliano Pontil
C. Ciliberto
OT
24
130
0
30 May 2018
Relating Leverage Scores and Density using Regularized Christoffel
  Functions
Relating Leverage Scores and Density using Regularized Christoffel Functions
Edouard Pauwels
Francis R. Bach
Jean-Philippe Vert
13
20
0
21 May 2018
Random Fourier Features for Kernel Ridge Regression: Approximation
  Bounds and Statistical Guarantees
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
H. Avron
Michael Kapralov
Cameron Musco
Christopher Musco
A. Velingker
A. Zandieh
6
155
0
26 Apr 2018
Instance Optimal Decoding and the Restricted Isometry Property
Instance Optimal Decoding and the Restricted Isometry Property
Nicolas Keriven
Rémi Gribonval
19
8
0
27 Feb 2018
Intriguing Properties of Randomly Weighted Networks: Generalizing While
  Learning Next to Nothing
Intriguing Properties of Randomly Weighted Networks: Generalizing While Learning Next to Nothing
Amir Rosenfeld
John K. Tsotsos
MLT
24
51
0
02 Feb 2018
Exponential convergence of testing error for stochastic gradient methods
Exponential convergence of testing error for stochastic gradient methods
Loucas Pillaud-Vivien
Alessandro Rudi
Francis R. Bach
19
31
0
13 Dec 2017
Invariance of Weight Distributions in Rectified MLPs
Invariance of Weight Distributions in Rectified MLPs
Russell Tsuchida
Farbod Roosta-Khorasani
M. Gallagher
MLT
24
35
0
24 Nov 2017
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Zi Wang
Clement Gehring
Pushmeet Kohli
Stefanie Jegelka
UQCV
9
209
0
05 Jun 2017
Orthogonal Random Features
Orthogonal Random Features
Felix X. Yu
A. Suresh
K. Choromanski
D. Holtmann-Rice
Sanjiv Kumar
19
217
0
28 Oct 2016
Sharp analysis of low-rank kernel matrix approximations
Sharp analysis of low-rank kernel matrix approximations
Francis R. Bach
86
277
0
09 Aug 2012
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