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Learning with Group Invariant Features: A Kernel Perspective
v1v2 (latest)

Learning with Group Invariant Features: A Kernel Perspective

8 June 2015
Youssef Mroueh
S. Voinea
T. Poggio
    VLM
ArXiv (abs)PDFHTML

Papers citing "Learning with Group Invariant Features: A Kernel Perspective"

11 / 11 papers shown
Title
The good, the bad and the ugly sides of data augmentation: An implicit
  spectral regularization perspective
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective
Chi-Heng Lin
Chiraag Kaushik
Eva L. Dyer
Vidya Muthukumar
103
31
0
10 Oct 2022
Understanding the Generalization Benefit of Model Invariance from a Data
  Perspective
Understanding the Generalization Benefit of Model Invariance from a Data Perspective
Sicheng Zhu
Bang An
Furong Huang
51
26
0
10 Nov 2021
Provably Strict Generalisation Benefit for Invariance in Kernel Methods
Provably Strict Generalisation Benefit for Invariance in Kernel Methods
Bryn Elesedy
88
27
0
04 Jun 2021
Provably Strict Generalisation Benefit for Equivariant Models
Provably Strict Generalisation Benefit for Equivariant Models
Bryn Elesedy
Sheheryar Zaidi
AI4CE
98
88
0
20 Feb 2021
Convex Representation Learning for Generalized Invariance in
  Semi-Inner-Product Space
Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space
Yingyi Ma
Vignesh Ganapathiraman
Yaoliang Yu
Xinhua Zhang
32
1
0
25 Apr 2020
Biased Stochastic First-Order Methods for Conditional Stochastic
  Optimization and Applications in Meta Learning
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning
Yifan Hu
Siqi Zhang
Xin Chen
Niao He
ODL
109
56
0
25 Feb 2020
A Kernel Theory of Modern Data Augmentation
A Kernel Theory of Modern Data Augmentation
Tri Dao
Albert Gu
Alexander J. Ratner
Virginia Smith
Christopher De Sa
Christopher Ré
120
193
0
16 Mar 2018
Variational Inference of Disentangled Latent Concepts from Unlabeled
  Observations
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations
Abhishek Kumar
P. Sattigeri
Avinash Balakrishnan
BDLDRL
120
523
0
02 Nov 2017
Group Invariance, Stability to Deformations, and Complexity of Deep
  Convolutional Representations
Group Invariance, Stability to Deformations, and Complexity of Deep Convolutional Representations
A. Bietti
Julien Mairal
68
8
0
09 Jun 2017
Local Group Invariant Representations via Orbit Embeddings
Local Group Invariant Representations via Orbit Embeddings
Anant Raj
Abhishek Kumar
Youssef Mroueh
Tom Fletcher
Bernhard Schölkopf
91
38
0
06 Dec 2016
Learning from Conditional Distributions via Dual Embeddings
Learning from Conditional Distributions via Dual Embeddings
Bo Dai
Niao He
Yunpeng Pan
Byron Boots
Le Song
88
21
0
15 Jul 2016
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