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. 2111.04579
  4. Cited By
Information-Theoretic Bayes Risk Lower Bounds for Realizable Models

Information-Theoretic Bayes Risk Lower Bounds for Realizable Models

8 November 2021
M. Nokleby
Ahmad Beirami
ArXivPDFHTML

Papers citing "Information-Theoretic Bayes Risk Lower Bounds for Realizable Models"

14 / 14 papers shown
Title
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of
  Overparameterized Machine Learning
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning
Yehuda Dar
Vidya Muthukumar
Richard G. Baraniuk
71
72
0
06 Sep 2021
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate
  bounds that handle general VC classes
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes
Peter Grünwald
Thomas Steinke
Lydia Zakynthinou
54
30
0
17 Jun 2021
Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning
Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning
Hassan Hafez-Kolahi
Behrad Moniri
S. Kasaei
M. Baghshah
106
12
0
10 May 2021
Minimum Excess Risk in Bayesian Learning
Minimum Excess Risk in Bayesian Learning
Aolin Xu
Maxim Raginsky
320
39
0
29 Dec 2020
On the role of data in PAC-Bayes bounds
On the role of data in PAC-Bayes bounds
Gintare Karolina Dziugaite
Kyle Hsu
W. Gharbieh
Gabriel Arpino
Daniel M. Roy
56
78
0
19 Jun 2020
Reasoning About Generalization via Conditional Mutual Information
Reasoning About Generalization via Conditional Mutual Information
Thomas Steinke
Lydia Zakynthinou
125
165
0
24 Jan 2020
Deep Double Descent: Where Bigger Models and More Data Hurt
Deep Double Descent: Where Bigger Models and More Data Hurt
Preetum Nakkiran
Gal Kaplun
Yamini Bansal
Tristan Yang
Boaz Barak
Ilya Sutskever
119
935
0
04 Dec 2019
Benign Overfitting in Linear Regression
Benign Overfitting in Linear Regression
Peter L. Bartlett
Philip M. Long
Gábor Lugosi
Alexander Tsigler
MLT
67
777
0
26 Jun 2019
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for
  Neural Networks
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
Behnam Neyshabur
Srinadh Bhojanapalli
Nathan Srebro
77
605
0
29 Jul 2017
Spectrally-normalized margin bounds for neural networks
Spectrally-normalized margin bounds for neural networks
Peter L. Bartlett
Dylan J. Foster
Matus Telgarsky
ODL
179
1,216
0
26 Jun 2017
Information-theoretic analysis of generalization capability of learning
  algorithms
Information-theoretic analysis of generalization capability of learning algorithms
Aolin Xu
Maxim Raginsky
141
445
0
22 May 2017
Understanding deep learning requires rethinking generalization
Understanding deep learning requires rethinking generalization
Chiyuan Zhang
Samy Bengio
Moritz Hardt
Benjamin Recht
Oriol Vinyals
HAI
312
4,623
0
10 Nov 2016
Rate-Distortion Bounds on Bayes Risk in Supervised Learning
Rate-Distortion Bounds on Bayes Risk in Supervised Learning
M. Nokleby
Ahmad Beirami
Robert Calderbank
28
0
0
08 May 2016
Fast rates in statistical and online learning
Fast rates in statistical and online learning
T. Erven
Peter Grünwald
Nishant A. Mehta
Mark D. Reid
Robert C. Williamson
132
108
0
09 Jul 2015
1