ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1605.06265
  4. Cited By
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks

End-to-End Kernel Learning with Supervised Convolutional Kernel Networks

20 May 2016
Julien Mairal
    SSL
ArXivPDFHTML

Papers citing "End-to-End Kernel Learning with Supervised Convolutional Kernel Networks"

19 / 19 papers shown
Title
Descriptive Kernel Convolution Network with Improved Random Walk Kernel
Descriptive Kernel Convolution Network with Improved Random Walk Kernel
Meng-Chieh Lee
Lingxiao Zhao
L. Akoglu
18
3
0
08 Feb 2024
Higher Order Gauge Equivariant CNNs on Riemannian Manifolds and
  Applications
Higher Order Gauge Equivariant CNNs on Riemannian Manifolds and Applications
Gianfranco Cortés
Yue Yu
R. Chen
Melissa S. Armstrong
David E Vaillancourt
B. Vemuri
29
1
0
26 May 2023
COmic: Convolutional Kernel Networks for Interpretable End-to-End
  Learning on (Multi-)Omics Data
COmic: Convolutional Kernel Networks for Interpretable End-to-End Learning on (Multi-)Omics Data
Jonas C. Ditz
Bernhard Reuter
Nícolas Pfeifer
19
1
0
02 Dec 2022
Frequency Dropout: Feature-Level Regularization via Randomized Filtering
Frequency Dropout: Feature-Level Regularization via Randomized Filtering
Mobarakol Islam
Ben Glocker
OOD
32
6
0
20 Sep 2022
Generalized Reference Kernel for One-class Classification
Generalized Reference Kernel for One-class Classification
Jenni Raitoharju
Alexandros Iosifidis
11
2
0
01 May 2022
On the Spectral Bias of Convolutional Neural Tangent and Gaussian
  Process Kernels
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels
Amnon Geifman
Meirav Galun
David Jacobs
Ronen Basri
19
13
0
17 Mar 2022
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Liyao (Mars) Gao
Guang Lin
Wei-wei Zhu
17
8
0
22 Nov 2021
Learning with convolution and pooling operations in kernel methods
Learning with convolution and pooling operations in kernel methods
Theodor Misiakiewicz
Song Mei
MLT
15
29
0
16 Nov 2021
Convolutional Motif Kernel Networks
Convolutional Motif Kernel Networks
Jonas C. Ditz
Bernhard Reuter
N. Pfeifer
FAtt
10
2
0
03 Nov 2021
Locality defeats the curse of dimensionality in convolutional
  teacher-student scenarios
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios
Alessandro Favero
Francesco Cagnetta
M. Wyart
22
31
0
16 Jun 2021
Learning Multiscale Convolutional Dictionaries for Image Reconstruction
Learning Multiscale Convolutional Dictionaries for Image Reconstruction
Tianlin Liu
Anadi Chaman
David Belius
Ivan Dokmanić
25
27
0
25 Nov 2020
Parametric machines: a fresh approach to architecture search
Parametric machines: a fresh approach to architecture search
Pietro Vertechi
M. Bergomi
19
2
0
06 Jul 2020
Discriminative Clustering with Representation Learning with any Ratio of
  Labeled to Unlabeled Data
Discriminative Clustering with Representation Learning with any Ratio of Labeled to Unlabeled Data
Corinne Jones
Vincent Roulet
Zaïd Harchaoui
28
1
0
30 Dec 2019
Kernel-Based Approaches for Sequence Modeling: Connections to Neural
  Methods
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
Kevin J Liang
Guoyin Wang
Yitong Li
Ricardo Henao
Lawrence Carin
18
2
0
09 Oct 2019
A Kernel Perspective for Regularizing Deep Neural Networks
A Kernel Perspective for Regularizing Deep Neural Networks
A. Bietti
Grégoire Mialon
Dexiong Chen
Julien Mairal
11
15
0
30 Sep 2018
Generalizing the Convolution Operator in Convolutional Neural Networks
Generalizing the Convolution Operator in Convolutional Neural Networks
Kamaledin Ghiasi-Shirazi
11
38
0
14 Jul 2017
Supervised Deep Sparse Coding Networks
Supervised Deep Sparse Coding Networks
Xiaoxia Sun
Nasser M. Nasrabadi
T. Tran
BDL
19
15
0
29 Jan 2017
Stochastic Optimization with Variance Reduction for Infinite Datasets
  with Finite-Sum Structure
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure
A. Bietti
Julien Mairal
32
36
0
04 Oct 2016
An Inexact Variable Metric Proximal Point Algorithm for Generic
  Quasi-Newton Acceleration
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration
Hongzhou Lin
Julien Mairal
Zaïd Harchaoui
21
13
0
04 Oct 2016
1