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Nonparametric Estimation of Renyi Divergence and Friends
v1v2 (latest)

Nonparametric Estimation of Renyi Divergence and Friends

12 February 2014
A. Krishnamurthy
Kirthevasan Kandasamy
Barnabás Póczós
Larry A. Wasserman
ArXiv (abs)PDFHTML

Papers citing "Nonparametric Estimation of Renyi Divergence and Friends"

42 / 42 papers shown
Title
Variational Weighting for Kernel Density Ratios
Variational Weighting for Kernel Density Ratios
Sangwoong Yoon
Frank C. Park
Gunsu S Yun
Iljung Kim
Yung-Kyun Noh
23
0
0
06 Nov 2023
DP-Auditorium: a Large Scale Library for Auditing Differential Privacy
DP-Auditorium: a Large Scale Library for Auditing Differential Privacy
William Kong
Andrés Munoz Medina
Mónica Ribero
Umar Syed
70
4
0
10 Jul 2023
When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev
  Embedding and Minimax Optimality
When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev Embedding and Minimax Optimality
Jose H. Blanchet
Haoxuan Chen
Yiping Lu
Lexing Ying
71
4
0
25 May 2023
The Representation Jensen-Shannon Divergence
The Representation Jensen-Shannon Divergence
J. Hoyos-Osorio
Santiago Posso-Murillo
L. S. Giraldo
159
8
0
25 May 2023
The Fundamental Limits of Structure-Agnostic Functional Estimation
The Fundamental Limits of Structure-Agnostic Functional Estimation
Sivaraman Balakrishnan
Edward H. Kennedy
Larry A. Wasserman
70
11
0
06 May 2023
Lower Bounds for Rényi Differential Privacy in a Black-Box Setting
Lower Bounds for Rényi Differential Privacy in a Black-Box Setting
T. Kutta
Önder Askin
Martin Dunsche
70
4
0
09 Dec 2022
Collaborative likelihood-ratio estimation over graphs
Collaborative likelihood-ratio estimation over graphs
Alejandro de la Concha
Nicolas Vayatis
Argyris Kalogeratos
69
1
0
28 May 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
55
5
0
27 May 2022
Plugin Estimation of Smooth Optimal Transport Maps
Plugin Estimation of Smooth Optimal Transport Maps
Tudor Manole
Sivaraman Balakrishnan
Jonathan Niles-Weed
Larry A. Wasserman
OT
89
100
0
26 Jul 2021
Non-Asymptotic Performance Guarantees for Neural Estimation of
  $\mathsf{f}$-Divergences
Non-Asymptotic Performance Guarantees for Neural Estimation of f\mathsf{f}f-Divergences
Sreejith Sreekumar
Zhengxin Zhang
Ziv Goldfeld
FedML
72
18
0
11 Mar 2021
On the consistency of the Kozachenko-Leonenko entropy estimate
On the consistency of the Kozachenko-Leonenko entropy estimate
Luc Devroye
László Gyorfi
35
4
0
25 Feb 2021
$(f,Γ)$-Divergences: Interpolating between $f$-Divergences and
  Integral Probability Metrics
(f,Γ)(f,Γ)(f,Γ)-Divergences: Interpolating between fff-Divergences and Integral Probability Metrics
Jeremiah Birrell
P. Dupuis
Markos A. Katsoulakis
Yannis Pantazis
Luc Rey-Bellet
52
8
0
11 Nov 2020
Mutual Information for Explainable Deep Learning of Multiscale Systems
Mutual Information for Explainable Deep Learning of Multiscale Systems
S. Taverniers
E. Hall
Markos A. Katsoulakis
D. Tartakovsky
37
15
0
07 Sep 2020
Minimax Optimal Estimation of KL Divergence for Continuous Distributions
Minimax Optimal Estimation of KL Divergence for Continuous Distributions
Puning Zhao
Lifeng Lai
65
21
0
26 Feb 2020
Conditional Shannon, Réyni, and Tsallis entropies estimation and
  asymptotic limits: discrete case
Conditional Shannon, Réyni, and Tsallis entropies estimation and asymptotic limits: discrete case
Ba Amadou Diadie
Lo Gane Samb
17
0
0
16 Feb 2020
Non parametric estimation of residual-past entropy, mean residual-past
  lifetime, residual-past inaccuracy measure and asymptotic limits
Non parametric estimation of residual-past entropy, mean residual-past lifetime, residual-past inaccuracy measure and asymptotic limits
Ba Amadou Diadie
13
0
0
30 Nov 2019
Updating Variational Bayes: Fast sequential posterior inference
Updating Variational Bayes: Fast sequential posterior inference
Nathaniel Tomasetti
Catherine S. Forbes
Anastasios Panagiotelis
41
9
0
01 Aug 2019
From Blackwell Dominance in Large Samples to Renyi Divergences and Back
  Again
From Blackwell Dominance in Large Samples to Renyi Divergences and Back Again
Xiaosheng Mu
L. Pomatto
P. Strack
Omer Tamuz
30
3
0
06 Jun 2019
Practical and Consistent Estimation of f-Divergences
Practical and Consistent Estimation of f-Divergences
Paul Kishan Rubenstein
Olivier Bousquet
Josip Djolonga
C. Riquelme
Ilya O. Tolstikhin
70
45
0
27 May 2019
Geometric Estimation of Multivariate Dependency
Geometric Estimation of Multivariate Dependency
Salimeh Yasaei Sekeh
Alfred Hero
45
11
0
21 May 2019
Entropies and their Asymptotic Theory in the discrete case
Entropies and their Asymptotic Theory in the discrete case
Amadou Diadié Ba
G. Lo
21
2
0
19 Mar 2019
Minimax Estimation of Quadratic Fourier Functionals
Minimax Estimation of Quadratic Fourier Functionals
Shashank Singh
Bharath K. Sriperumbudur
Barnabás Póczós
106
5
0
30 Mar 2018
Scalable Mutual Information Estimation using Dependence Graphs
Scalable Mutual Information Estimation using Dependence Graphs
M. Noshad
Yu Zeng
Alfred Hero
77
73
0
27 Jan 2018
The Nearest Neighbor Information Estimator is Adaptively Near Minimax
  Rate-Optimal
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal
Jiantao Jiao
Weihao Gao
Yanjun Han
78
47
0
23 Nov 2017
Optimal rates of entropy estimation over Lipschitz balls
Optimal rates of entropy estimation over Lipschitz balls
Yanjun Han
Jiantao Jiao
Tsachy Weissman
Yihong Wu
114
73
0
06 Nov 2017
Rate-optimal Meta Learning of Classification Error
Rate-optimal Meta Learning of Classification Error
M. Iranzad
Alfred Hero
32
5
0
31 Oct 2017
Nonparanormal Information Estimation
Nonparanormal Information Estimation
Shashank Singh
Barnabás Póczós
136
20
0
24 Feb 2017
Ensemble Estimation of Generalized Mutual Information with Applications
  to Genomics
Ensemble Estimation of Generalized Mutual Information with Applications to Genomics
Kevin R. Moon
K. Sricharan
Alfred Hero
45
9
0
27 Jan 2017
Information Theoretic Structure Learning with Confidence
Information Theoretic Structure Learning with Confidence
Kevin R. Moon
M. Noshad
Salimeh Yasaei Sekeh
Alfred Hero
43
18
0
13 Sep 2016
Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional
  Estimators
Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators
Shashank Singh
Barnabás Póczós
80
53
0
05 Jun 2016
Efficient Nonparametric Smoothness Estimation
Efficient Nonparametric Smoothness Estimation
Shashank Singh
S. Du
Barnabás Póczós
72
4
0
19 May 2016
Consistency Bands for divergences measures
Consistency Bands for divergences measures
Amadou Diadié Ba
46
0
0
14 Apr 2016
Demystifying Fixed k-Nearest Neighbor Information Estimators
Demystifying Fixed k-Nearest Neighbor Information Estimators
Weihao Gao
Sewoong Oh
Pramod Viswanath
103
138
0
11 Apr 2016
Exponential Concentration of a Density Functional Estimator
Exponential Concentration of a Density Functional Estimator
Shashank Singh
Barnabás Póczós
64
53
0
28 Mar 2016
Analysis of k-Nearest Neighbor Distances with Application to Entropy
  Estimation
Analysis of k-Nearest Neighbor Distances with Application to Entropy Estimation
Shashank Singh
Barnabás Póczós
72
37
0
28 Mar 2016
A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model
  Evaluation
A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation
Qiang Liu
Jason D. Lee
Michael I. Jordan
150
486
0
10 Feb 2016
Linear-time Learning on Distributions with Approximate Kernel Embeddings
Linear-time Learning on Distributions with Approximate Kernel Embeddings
Danica J. Sutherland
Junier B. Oliva
Barnabás Póczós
J. Schneider
61
18
0
24 Sep 2015
Meta learning of bounds on the Bayes classifier error
Meta learning of bounds on the Bayes classifier error
Kevin R. Moon
V. Delouille
Alfred Hero
73
15
0
27 Apr 2015
Influence Functions for Machine Learning: Nonparametric Estimators for
  Entropies, Divergences and Mutual Informations
Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations
Kirthevasan Kandasamy
A. Krishnamurthy
Barnabás Póczós
Larry A. Wasserman
J. M. Robins
TDI
112
20
0
17 Nov 2014
Multivariate f-Divergence Estimation With Confidence
Multivariate f-Divergence Estimation With Confidence
Kevin R. Moon
Alfred Hero
78
71
0
07 Nov 2014
On Estimating $L_2^2$ Divergence
On Estimating L22L_2^2L22​ Divergence
A. Krishnamurthy
Kirthevasan Kandasamy
Barnabás Póczós
Larry A. Wasserman
71
7
0
30 Oct 2014
Rate of convergence in the maximum likelihood estimation for partial
  discrete parameter, with applications to the cluster analysis and philology
Rate of convergence in the maximum likelihood estimation for partial discrete parameter, with applications to the cluster analysis and philology
E.Ostrovsky
L.Sirota
A.Zeldin
37
1
0
26 Feb 2014
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