Bharath K. Sriperumbudur

发表

A Fast, Consistent Kernel Two-Sample Test

Zaïd Harchaoui, Kenji Fukumizu, Arthur Gretton, 2009, NIPS.

Universality, Characteristic Kernels and RKHS Embedding of Measures

Kenji Fukumizu, Gert R. G. Lanckriet, Bharath K. Sriperumbudur, 2010, J. Mach. Learn. Res..

Convergence guarantees for kernel-based quadrature rules in misspecified settings

Kenji Fukumizu, Bharath K. Sriperumbudur, Motonobu Kanagawa, 2016, NIPS.

Minimax Estimation of Kernel Mean Embeddings

Krikamol Muandet, Bharath K. Sriperumbudur, Ilya O. Tolstikhin, 2016, J. Mach. Learn. Res..

Characteristic and Universal Tensor Product Kernels pdf

Zoltán Szabó, Bharath K. Sriperumbudur, Z. Szabó, 2017, J. Mach. Learn. Res..

Regression on Probability Measures: A Simple and Consistent Algorithm

Barnabás Póczos, Arthur Gretton, Bharath K. Sriperumbudur, 2015 .

A Proof of Convergence of the Concave-Convex Procedure Using Zangwill's Theory

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, 2012, Neural Computation.

Kernel Mean Estimation via Spectral Filtering

Bernhard Schölkopf, Krikamol Muandet, Bharath K. Sriperumbudur, 2014, NIPS.

Optimal Rates for Random Fourier Feature Approximations

Bharath K. Sriperumbudur, Z Szabo, 2015 .

Ultrahigh Dimensional Feature Screening via RKHS Embeddings

Krishnakumar Balasubramanian, Guy Lebanon, Bharath K. Sriperumbudur, 2013, AISTATS.

Optimal Rates for Random Fourier Features

Zoltán Szabó, Bharath K. Sriperumbudur, Z. Szabó, 2015, NIPS.

A note on integral probability metrics and $\phi$-divergences pdf

Bernhard Schölkopf, Kenji Fukumizu, Arthur Gretton, 2009, ArXiv.

Optimal kernel choice for large-scale two-sample tests

Sivaraman Balakrishnan, Kenji Fukumizu, Arthur Gretton, 2012, NIPS.

Distribution Regression with Minimax-Optimal Guarantee

Barnabás Póczos, Arthur Gretton, Bharath K. Sriperumbudur, 2016 .

Learning Theory for Vector-Valued Distribution Regression

Barnabás Póczos, Arthur Gretton, Bharath K. Sriperumbudur, 2015 .

Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint

Kenji Fukumizu, Gert R. G. Lanckriet, Bharath K. Sriperumbudur, 2011, NIPS.

Consistent Distribution Regression via Mean Embedding

Barnabás Póczos, Arthur Gretton, Bharath K. Sriperumbudur, 2014 .

On integral probability metrics, φ-divergences and binary classification

Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, 2009, 0901.2698.

Local minimax rates for closeness testing of discrete distributions pdf

Alexandra Carpentier, Bharath K. Sriperumbudur, Joseph Lam-Weil, 2019, ArXiv.

Kernel Mean Embedding of Distributions: A Review and Beyonds pdf

Bernhard Schölkopf, Kenji Fukumizu, Krikamol Muandet, 2016, Found. Trends Mach. Learn..

Equivalence of distance-based and RKHS-based statistics in hypothesis testing pdf

Kenji Fukumizu, Arthur Gretton, Dino Sejdinovic, 2012, ArXiv.

Nearest Neighbor Prototyping for Sparse and Scalable Support Vector Machines

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, 2007 .

Generalized Clustering via Kernel Embeddings

Bernhard Schölkopf, Ulrike von Luxburg, Arthur Gretton, 2009, KI.

Hypothesis testing using pairwise distances and associated kernels pdf

Kenji Fukumizu, Arthur Gretton, Dino Sejdinovic, 2012, ICML.

Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions

Bernhard Schölkopf, Kenji Fukumizu, Arthur Gretton, 2009, NIPS.

Consistent, Two-Stage Sampled Distribution Regression via Mean Embedding pdf

Barnabás Póczos, Arthur Gretton, Zoltán Szabó, 2014, ArXiv.

Minimax Estimation of Quadratic Fourier Functionals pdf

Barnabás Póczos, Shashank Singh, Bharath K. Sriperumbudur, 2018, ArXiv.

Consistency and Rates for Clustering with DBSCAN

Ingo Steinwart, Bharath K. Sriperumbudur, Ingo Steinwart, 2012, AISTATS.

Mixture density estimation via Hilbert space embedding of measures

Bharath K. Sriperumbudur, 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

Kernel Mean Shrinkage Estimators pdf

Bernhard Schölkopf, Kenji Fukumizu, Arthur Gretton, 2014, J. Mach. Learn. Res..

Sparse eigen methods by D.C. programming

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, David A. Torres, 2007, ICML '07.

Gaussian Sketching yields a J-L Lemma in RKHS

Bharath K. Sriperumbudur, Samory Kpotufe, Samory Kpotufe, 2019, AISTATS.

Metric embedding for kernel classification rules

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, Omer A. Lang, 2008, ICML '08.

Hilbert Space Embeddings and Metrics on Probability Measures

Bernhard Schölkopf, Kenji Fukumizu, Arthur Gretton, 2009, J. Mach. Learn. Res..

Performance Guarantees for Random Fourier Features - Limitations and Merits

Bharath K. Sriperumbudur, Z Szabo, 2015 .

Density Estimation in Infinite Dimensional Exponential Families

Aapo Hyvärinen, Kenji Fukumizu, Arthur Gretton, 2013, J. Mach. Learn. Res..

A majorization-minimization approach to the sparse generalized eigenvalue problem

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, David A. Torres, 2011, Machine Learning.

Two-stage sampled learning theory on distributions

Barnabás Póczos, Arthur Gretton, Zoltán Szabó, 2015, AISTATS.

Non-parametric estimation of integral probability metrics

Bernhard Schölkopf, Kenji Fukumizu, Arthur Gretton, 2010, 2010 IEEE International Symposium on Information Theory.

On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions pdf

Prateek Jain, Harish Karnick, Purushottam Kar, 2013, ICML.

Distribution Regression - the Set Kernel Heuristic is Consistent

Barnabás Póczos, Arthur Gretton, Bharath K. Sriperumbudur, 2014 .

On the Convergence of the Concave-Convex Procedure

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, G. Lanckriet, 2009, NIPS.

Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels

Bernhard Schölkopf, Bharath K. Sriperumbudur, Ilya O. Tolstikhin, 2016, NIPS.

Kernel Mean Estimation and Stein Effect

Bernhard Schölkopf, Kenji Fukumizu, Arthur Gretton, 2013, ICML.

Characteristic Kernels on Groups and Semigroups

Bernhard Schölkopf, Kenji Fukumizu, Arthur Gretton, 2008, NIPS.

Vector-valued Distribution Regression - Keep It Simple and Consistent

Barnabás Póczos, Arthur Gretton, Bharath K. Sriperumbudur, 2015 .

Injective Hilbert Space Embeddings of Probability Measures

Bernhard Schölkopf, Kenji Fukumizu, Arthur Gretton, 2008, COLT.

On Kernel Derivative Approximation with Random Fourier Features

Zoltán Szabó, Bharath K. Sriperumbudur, Z. Szabó, 2018, AISTATS.

Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings

Kenji Fukumizu, Bharath K. Sriperumbudur, Motonobu Kanagawa, 2017, Foundations of Computational Mathematics.

Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences pdf

Dino Sejdinovic, Philipp Hennig, Bharath K. Sriperumbudur, 2018, ArXiv.

Optimal Rates for Random Fourier Feature Kernel Approximations

Bharath K. Sriperumbudur, Z Szabo, 2015 .

Cycle Consistent Probability Divergences Across Different Spaces pdf

Youssef Mroueh, Ziv Goldfeld, Zhengxin Zhang, 2021, AISTATS.

On the empirical estimation of integral probability metrics

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, K. Fukumizu, 2012 .

On the optimal estimation of probability measures in weak and strong topologies

Bharath K. Sriperumbudur, 2013, 1310.8240.

Discussion of: Brownian distance covariance

Bharath K. Sriperumbudur, K. Fukumizu, A. Gretton, 2009, 1010.0836.

RKHS Representation of Measures Applied to Homogeneity, Independence, and Fourier Optics

Bharath K. Sriperumbudur, S. Smale, B. Schölkopf, 2008 .

Ja n 20 09 A Note on Integral Probability Metrics and φ-divergences

Bharath K. Sriperumbudur, B. Schölkopf, K. Fukumizu, 2009 .

The Sparse Eigenvalue Problem

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, David A. Torres, 2009 .

A D.C. Programming Approach to the Sparse Generalized Eigenvalue Problem

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, David A. Torres, 2009, 0901.1504.

Statistical Invariance of Betti Numbers in the Thermodynamic Regime.

Bharath K. Sriperumbudur, K. Fukumizu, S. Kuriki, 2020 .

On Distance and Kernel Measures of Conditional Independence

Bharath K. Sriperumbudur, T. Sheng, 2019, 1912.01103.

Approximate Kernel PCA Using Random Features: Computational vs. Statistical Trade-off

Bharath K. Sriperumbudur, Nicholas Sterge, 2017, 1706.06296.

A D.C. Programming Approach to the Sparse Generalized Eigenvalue Problem

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, David A. Torres, 2009, 0901.1504.

Learning on Distributions

Barnabás Póczos, Arthur Gretton, Zoltán Szabó, 2014 .

An Introduction to Wishart Matrix Moments

Ryan P. Adams, Bharath K. Sriperumbudur, R. Zadeh, 2018 .

Vector-valued distribution regression: a simple and consistent approach

Bharath K. Sriperumbudur, B. Póczos, A. Gretton, 2014 .

Mean Shrinkage Estimation for High-Dimensional Diagonal Natural Exponential Families.

Bharath K. Sriperumbudur, D. Richards, Nikolas Siapoutis, 2020 .

Adaptive Clustering Using Kernel Density Estimators

Ingo Steinwart, Bharath K. Sriperumbudur, Ingo Steinwart, 2017, 1708.05254.

Consistent Vector-valued Regression on Probability Measures

Bharath K. Sriperumbudur, B. Póczos, A. Gretton, 2015 .

Optimal Prediction for Additive Function-on-Function Regression

Bharath K. Sriperumbudur, M. Reimherr, Bahaeddine Taoufik, 2017, 1708.03372.

S T ] 4 N ov 2 01 5 Optimal Rates for Random Fourier Features

Bharath K. Sriperumbudur, 2018 .

Robust Topological Inference in the Presence of Outliers

Bharath K. Sriperumbudur, K. Fukumizu, S. Kuriki, 2022, ArXiv.

Unified RKHS Methodology and Analysis for Functional Linear and Single-Index Models

Bharath K. Sriperumbudur, K. Balasubramanian, H. Muller, 2022, 2206.03975.

Metric Embedding for Nearest Neighbor Classification

Bharath K. Sriperumbudur, G. Lanckriet, 2007, 0706.3499.

Shrinkage Estimation for the Diagonal Multivariate Exponential Families

Bharath K. Sriperumbudur, D. Richards, Nikolas Siapoutis, 2020, 2010.08071.

Robust Persistence Diagrams using Reproducing Kernels

Bharath K. Sriperumbudur, K. Fukumizu, S. Kuriki, 2020, NeurIPS.

Statistical Consistency of Kernel PCA with Random Features

Bharath K. Sriperumbudur, Nicholas Sterge, 2017 .

Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings

Bharath K. Sriperumbudur, K. Fukumizu, Motonobu Kanagawa, 2019, Foundations of Computational Mathematics.

Regularized Stein Variational Gradient Flow

Bharath K. Sriperumbudur, K. Balasubramanian, Jianfeng Lu, 2022, ArXiv.

Gromov-Wasserstein Distances: Entropic Regularization, Duality, and Sample Complexity

Bharath K. Sriperumbudur, Youssef Mroueh, Ziv Goldfeld, 2022, 2212.12848.

On the Limits of Topological Data Analysis for Statistical Inference

Bharath K. Sriperumbudur, K. Fukumizu, S. Kuriki, 2020, 2001.00220.

Supplementary Material to Kernel Mean Estimation and Stein Effect

Bharath K. Sriperumbudur, B. Schölkopf, K. Fukumizu, 2014 .

Learning Theory for Distribution Regression

Arthur Gretton, Zoltan Szabo, Barnabas Poczos, 2014, J. Mach. Learn. Res..

Gromov-Wasserstein Distances: Entropic Regularization, Duality, and Sample Complexity

Bharath K. Sriperumbudur, Youssef Mroueh, Ziv Goldfeld, 2022, 2212.12848.

Two-stage sampled learning theory on distributions

Bharath K. Sriperumbudur, B. Póczos, A. Gretton, 2014, AISTATS.

Spectral Regularized Kernel Goodness-of-Fit Tests

Bharath K. Sriperumbudur, Bing Li, Omar Hagrass, 2023, 2308.04561.

Spectral Regularized Kernel Two-Sample Tests

Bharath K. Sriperumbudur, Bing Li, Omar Hagrass, 2022, ArXiv.

A majorization-minimization approach to the sparse generalized eigenvalue problem

Gert R. G. Lanckriet, Bharath K. Sriperumbudur, David A. Torres, 2011 .

Statistical Optimality and Computational Efficiency of Nyström Kernel PCA

Bharath K. Sriperumbudur, Nicholas Sterge, 2021, J. Mach. Learn. Res..

Kernel Sketching yields Kernel JL

Bharath K. Sriperumbudur, Samory Kpotufe, 2019, ArXiv.

Optimal function-on-scalar regression over complex domains

Matthew Reimherr, Bharath K. Sriperumbudur, Bharath Sriperumbudur, 2019, Electronic Journal of Statistics.

Kernel $\epsilon$-Greedy for Contextual Bandits

Bharath K. Sriperumbudur, Sakshi Arya, 2023, 2306.17329.

Equivalence of distance-based and RKHS-based statistics in hypothesis testing

Bharath K. Sriperumbudur, K. Fukumizu, A. Gretton, 2012, ArXiv.

On Distance and Kernel Measures of Conditional Independence

Bharath K. Sriperumbudur, T. Sheng, 2019, 1912.01103.

On Distance and Kernel Measures of Conditional Dependence

Bharath K. Sriperumbudur, T. Sheng, 2023, J. Mach. Learn. Res..

Approximate kernel PCA: Computational versus statistical trade-off

Bharath K. Sriperumbudur, Nicholas Sterge, 2022, The Annals of Statistics.

Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling

Lorenzo Rosasco, Alessandro Rudi, Bharath K. Sriperumbudur, 2019, AISTATS.

Two-stage sampled learning theory on distributions

Bharath K. Sriperumbudur, B. Póczos, A. Gretton, 2014, AISTATS.