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Information Theory with Kernel Methods

Information Theory with Kernel Methods

17 February 2022
Francis R. Bach
ArXivPDFHTML

Papers citing "Information Theory with Kernel Methods"

29 / 29 papers shown
Title
From Two Sample Testing to Singular Gaussian Discrimination
From Two Sample Testing to Singular Gaussian Discrimination
Leonardo P. M. Santoro
Kartik G. Waghmare
V. Panaretos
31
0
0
07 May 2025
Information-Theoretic Perspectives on Optimizers
Information-Theoretic Perspectives on Optimizers
Zhiquan Tan
Weiran Huang
FAtt
54
0
0
28 Feb 2025
Variational Inference on the Boolean Hypercube with the Quantum Entropy
Variational Inference on the Boolean Hypercube with the Quantum Entropy
Eliot Beyler
Francis Bach
39
0
0
17 Feb 2025
Does Representation Matter? Exploring Intermediate Layers in Large
  Language Models
Does Representation Matter? Exploring Intermediate Layers in Large Language Models
Oscar Skean
Md Rifat Arefin
Yann LeCun
Ravid Shwartz-Ziv
81
7
0
12 Dec 2024
Conditional Vendi Score: An Information-Theoretic Approach to Diversity
  Evaluation of Prompt-based Generative Models
Conditional Vendi Score: An Information-Theoretic Approach to Diversity Evaluation of Prompt-based Generative Models
Mohammad Jalali
Azim Ospanov
Amin Gohari
Farzan Farnia
EGVM
37
2
0
05 Nov 2024
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
Md Rifat Arefin
G. Subbaraj
Nicolas Angelard-Gontier
Yann LeCun
Irina Rish
Ravid Shwartz-Ziv
C. Pal
LRM
126
0
0
04 Nov 2024
Estimating the Spectral Moments of the Kernel Integral Operator from Finite Sample Matrices
Estimating the Spectral Moments of the Kernel Integral Operator from Finite Sample Matrices
Chanwoo Chun
SueYeon Chung
Daniel D. Lee
24
1
0
23 Oct 2024
A Trust-Region Method for Graphical Stein Variational Inference
A Trust-Region Method for Graphical Stein Variational Inference
Liam Pavlovic
David M. Rosen
25
0
0
21 Oct 2024
Asymptotically Optimal Change Detection for Unnormalized Pre- and Post-Change Distributions
Asymptotically Optimal Change Detection for Unnormalized Pre- and Post-Change Distributions
Arman Adibi
Sanjeev R. Kulkarni
H. V. Poor
T. Banerjee
Vahid Tarokh
25
0
0
18 Oct 2024
Exploring Information-Theoretic Metrics Associated with Neural Collapse in Supervised Training
Exploring Information-Theoretic Metrics Associated with Neural Collapse in Supervised Training
Kun Song
Zhiquan Tan
Bochao Zou
Jiansheng Chen
Huimin Ma
Weiran Huang
37
0
0
25 Sep 2024
Learning to Embed Distributions via Maximum Kernel Entropy
Learning to Embed Distributions via Maximum Kernel Entropy
Oleksii Kachaiev
Stefano Recanatesi
OOD
28
0
0
01 Aug 2024
Unveiling the Dynamics of Information Interplay in Supervised Learning
Unveiling the Dynamics of Information Interplay in Supervised Learning
Kun Song
Zhiquan Tan
Bochao Zou
Huimin Ma
Weiran Huang
30
1
0
06 Jun 2024
Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel
  Learning
Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning
Fan He
Mingzhe He
Lei Shi
Xiaolin Huang
Johan A. K. Suykens
31
1
0
03 Jun 2024
Kernel Language Entropy: Fine-grained Uncertainty Quantification for
  LLMs from Semantic Similarities
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities
Alexander Nikitin
Jannik Kossen
Yarin Gal
Pekka Marttinen
UQCV
47
23
0
30 May 2024
Extending Kernel Testing To General Designs
Extending Kernel Testing To General Designs
Anthony Ozier-Lafontaine
Franck Picard
Bertrand Michel
29
0
0
22 May 2024
A kernel-based analysis of Laplacian Eigenmaps
A kernel-based analysis of Laplacian Eigenmaps
Martin Wahl
27
2
0
26 Feb 2024
The Information of Large Language Model Geometry
The Information of Large Language Model Geometry
Zhiquan Tan
Chenghai Li
Weiran Huang
21
1
0
01 Feb 2024
Understanding Grokking Through A Robustness Viewpoint
Understanding Grokking Through A Robustness Viewpoint
Zhiquan Tan
Weiran Huang
AAML
OOD
35
6
0
11 Nov 2023
Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive
  Kernels
Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels
Fan He
Ming-qian He
Lei Shi
Xiaolin Huang
Johan A. K. Suykens
13
1
0
08 Oct 2023
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and
  Diffusion Models
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models
Yongchan Kwon
Eric Wu
K. Wu
James Zou
DiffM
TDI
18
53
0
02 Oct 2023
Information Flow in Self-Supervised Learning
Information Flow in Self-Supervised Learning
Zhiyuan Tan
Jingqin Yang
Weiran Huang
Yang Yuan
Yifan Zhang
SSL
25
13
0
29 Sep 2023
Theory and applications of the Sum-Of-Squares technique
Theory and applications of the Sum-Of-Squares technique
Francis R. Bach
Elisabetta Cornacchia
Luca Pesce
Giovanni Piccioli
10
2
0
28 Jun 2023
Matrix Information Theory for Self-Supervised Learning
Matrix Information Theory for Self-Supervised Learning
Yifan Zhang
Zhi-Hao Tan
Jingqin Yang
Weiran Huang
Yang Yuan
SSL
45
16
0
27 May 2023
The Representation Jensen-Shannon Divergence
The Representation Jensen-Shannon Divergence
J. Hoyos-Osorio
Santiago Posso-Murillo
L. S. Giraldo
40
6
0
25 May 2023
Distributed Gradient Descent for Functional Learning
Distributed Gradient Descent for Functional Learning
Zhan Yu
Jun Fan
Zhongjie Shi
Ding-Xuan Zhou
11
1
0
12 May 2023
Convergence Rates for Non-Log-Concave Sampling and Log-Partition
  Estimation
Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation
David Holzmüller
Francis R. Bach
29
8
0
06 Mar 2023
The Vendi Score: A Diversity Evaluation Metric for Machine Learning
The Vendi Score: A Diversity Evaluation Metric for Machine Learning
Dan Friedman
Adji Bousso Dieng
EGVM
80
108
0
05 Oct 2022
Sum-of-Squares Relaxations for Information Theory and Variational
  Inference
Sum-of-Squares Relaxations for Information Theory and Variational Inference
Francis R. Bach
14
11
0
27 Jun 2022
Auditing Differential Privacy in High Dimensions with the Kernel Quantum
  Rényi Divergence
Auditing Differential Privacy in High Dimensions with the Kernel Quantum Rényi Divergence
Carles Domingo-Enrich
Youssef Mroueh
11
5
0
27 May 2022
1