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

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1411.2635
  4. Cited By
A chain rule for the expected suprema of Gaussian processes

A chain rule for the expected suprema of Gaussian processes

10 November 2014
Andreas Maurer
ArXiv (abs)PDFHTML

Papers citing "A chain rule for the expected suprema of Gaussian processes"

18 / 18 papers shown
Title
On Generalization Bounds for Neural Networks with Low Rank Layers
On Generalization Bounds for Neural Networks with Low Rank Layers
Andrea Pinto
Akshay Rangamani
T. Poggio
AI4CE
161
1
0
20 Nov 2024
Sharing Knowledge in Multi-Task Deep Reinforcement Learning
Sharing Knowledge in Multi-Task Deep Reinforcement Learning
Carlo DÉramo
Davide Tateo
Andrea Bonarini
Marcello Restelli
Jan Peters
256
134
0
17 Jan 2024
A Theory of Multimodal Learning
A Theory of Multimodal Learning
Zhou Lu
119
17
0
21 Sep 2023
Nonlinear Meta-Learning Can Guarantee Faster Rates
Nonlinear Meta-Learning Can Guarantee Faster Rates
Dimitri Meunier
Zhu Li
Arthur Gretton
Samory Kpotufe
272
7
0
20 Jul 2023
Mastering Long-Tail Complexity on Graphs: Characterization, Learning,
  and Generalization
Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization
Haohui Wang
Baoyu Jing
Kaize Ding
Yada Zhu
Wei Cheng
Si Zhang
Yonghui Fan
Liqing Zhang
Dawei Zhou
131
11
0
17 May 2023
A Chain Rule for the Expected Suprema of Bernoulli Processes
A Chain Rule for the Expected Suprema of Bernoulli Processes
Y.-C. Chu
Maxim Raginsky
55
1
0
27 Apr 2023
Statistical learning on measures: an application to persistence diagrams
Statistical learning on measures: an application to persistence diagrams
Olympio Hacquard
Gilles Blanchard
Clément Levrard
188
3
0
15 Mar 2023
Provable Pathways: Learning Multiple Tasks over Multiple Paths
Provable Pathways: Learning Multiple Tasks over Multiple Paths
Yingcong Li
Samet Oymak
MoE
95
4
0
08 Mar 2023
Deep Safe Multi-Task Learning
Deep Safe Multi-Task Learning
Zhixiong Yue
Feiyang Ye
Yu Zhang
Christy Jie Liang
Ivor W. Tsang
82
3
0
20 Nov 2021
Learning an Explicit Hyperparameter Prediction Function Conditioned on
  Tasks
Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks
Jun Shu
Deyu Meng
Zongben Xu
133
8
0
06 Jul 2021
Consistency of invariance-based randomization tests
Consistency of invariance-based randomization tests
Guang Cheng
195
20
0
25 Apr 2021
On the Theory of Transfer Learning: The Importance of Task Diversity
On the Theory of Transfer Learning: The Importance of Task Diversity
Nilesh Tripuraneni
Michael I. Jordan
Chi Jin
194
228
0
20 Jun 2020
Learning finite-dimensional coding schemes with nonlinear reconstruction
  maps
Learning finite-dimensional coding schemes with nonlinear reconstruction maps
Jaeho Lee
Maxim Raginsky
78
9
0
23 Dec 2018
Autoencoding any Data through Kernel Autoencoders
Autoencoding any Data through Kernel Autoencoders
Pierre Laforgue
Nathan Huet
Florence dÁlché-Buc
86
20
0
28 May 2018
Learning to Multitask
Learning to Multitask
Yu Zhang
Ying Wei
Qiang Yang
196
53
0
19 May 2018
Bounds for Vector-Valued Function Estimation
Bounds for Vector-Valued Function Estimation
Andreas Maurer
Massimiliano Pontil
89
7
0
05 Jun 2016
Local Rademacher Complexity-based Learning Guarantees for Multi-Task
  Learning
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning
Niloofar Yousefi
Yunwen Lei
Matthias Kirchler
M. Mollaghasemi
G. Anagnostopoulos
155
29
0
18 Feb 2016
The Benefit of Multitask Representation Learning
The Benefit of Multitask Representation Learning
Andreas Maurer
Massimiliano Pontil
Bernardino Romera-Paredes
SSL
210
390
0
23 May 2015
1