Bharath K. Sriperumbudur

According to our database, Bharath K. Sriperumbudur authored at least 59 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

(De)-regularized Maximum Mean Discrepancy Gradient Flow.

Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur

CoRR, 2024

Nyström Kernel Stein Discrepancy.

Florian Kalinke, Zoltán Szabó, Bharath K. Sriperumbudur

CoRR, 2024

2023

Adaptive Clustering Using Kernel Density Estimators.

Ingo Steinwart, Bharath K. Sriperumbudur, Philipp Thomann

J. Mach. Learn. Res., 2023

On Distance and Kernel Measures of Conditional Dependence.

Tianhong Sheng, Bharath K. Sriperumbudur

J. Mach. Learn. Res., 2023

Kernel ε-Greedy for Contextual Bandits.

Sakshi Arya, Bharath K. Sriperumbudur

CoRR, 2023

2022

Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA.

Nicholas Sterge, Bharath K. Sriperumbudur

J. Mach. Learn. Res., 2022

Spectral Regularized Kernel Two-Sample Tests.

Omar Hagrass, Bharath K. Sriperumbudur, Bing Li

CoRR, 2022

Regularized Stein Variational Gradient Flow.

Ye He, Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Jianfeng Lu

CoRR, 2022

Robust Topological Inference in the Presence of Outliers.

Siddharth Vishwanath, Bharath K. Sriperumbudur, Kenji Fukumizu, Satoshi Kuriki

CoRR, 2022

Cycle Consistent Probability Divergences Across Different Spaces.

Zhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath K. Sriperumbudur

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2020

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

Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu

Found. Comput. Math., 2020

Robust Persistence Diagrams using Reproducing Kernels.

Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling.

Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Gaussian Sketching yields a J-L Lemma in RKHS.

Samory Kpotufe, Bharath K. Sriperumbudur

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Kernel Sketching yields Kernel JL.

Samory Kpotufe, Bharath K. Sriperumbudur

CoRR, 2019

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

Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi

CoRR, 2019

Local minimax rates for closeness testing of discrete distributions.

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

CoRR, 2019

On Kernel Derivative Approximation with Random Fourier Features.

Zoltán Szabó, Bharath K. Sriperumbudur

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

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

Motonobu Kanagawa, Philipp Hennig, Dino Sejdinovic, Bharath K. Sriperumbudur

CoRR, 2018

Minimax Estimation of Quadratic Fourier Functionals.

Shashank Singh, Bharath K. Sriperumbudur, Barnabás Póczos

CoRR, 2018

2017

Minimax Estimation of Kernel Mean Embeddings.

Ilya O. Tolstikhin, Bharath K. Sriperumbudur, Krikamol Muandet

J. Mach. Learn. Res., 2017

Characteristic and Universal Tensor Product Kernels.

Zoltán Szabó, Bharath K. Sriperumbudur

J. Mach. Learn. Res., 2017

Density Estimation in Infinite Dimensional Exponential Families.

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Aapo Hyvärinen, Revant Kumar

J. Mach. Learn. Res., 2017

Kernel Mean Embedding of Distributions: A Review and Beyond.

Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf

Found. Trends Mach. Learn., 2017

2016

Learning Theory for Distribution Regression.

Zoltán Szabó, Bharath K. Sriperumbudur, Barnabás Póczos, Arthur Gretton

J. Mach. Learn. Res., 2016

Kernel Mean Shrinkage Estimators.

Krikamol Muandet, Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf

J. Mach. Learn. Res., 2016

Kernel Mean Embedding of Distributions: A Review and Beyonds.

Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf

CoRR, 2016

Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels.

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

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Convergence guarantees for kernel-based quadrature rules in misspecified settings.

Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Optimal Rates for Random Fourier Features.

Bharath K. Sriperumbudur, Zoltán Szabó

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Two-stage sampled learning theory on distributions.

Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

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

Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur

CoRR, 2014

Kernel Mean Estimation via Spectral Filtering.

Krikamol Muandet, Bharath K. Sriperumbudur, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Kernel Mean Estimation and Stein Effect.

Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Kernel Mean Estimation and Stein's Effect.

Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf

CoRR, 2013

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

Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish Karnick

Proceedings of the 30th International Conference on Machine Learning, 2013

Ultrahigh Dimensional Feature Screening via RKHS Embeddings.

Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Guy Lebanon

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

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

Bharath K. Sriperumbudur, Gert R. G. Lanckriet

Neural Comput., 2012

Consistency and Rates for Clustering with DBSCAN.

Bharath K. Sriperumbudur, Ingo Steinwart

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

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

Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu

CoRR, 2012

Hypothesis testing using pairwise distances and associated kernels (with Appendix)

Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu

CoRR, 2012

Optimal kernel choice for large-scale two-sample tests.

Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Hypothesis testing using pairwise distances and associated kernels.

Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

A majorization-minimization approach to the sparse generalized eigenvalue problem.

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

Mach. Learn., 2011

Universality, Characteristic Kernels and RKHS Embedding of Measures.

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

J. Mach. Learn. Res., 2011

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

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

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Mixture density estimation via Hilbert space embedding of measures.

Bharath K. Sriperumbudur

Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

2010

Hilbert Space Embeddings and Metrics on Probability Measures.

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet

J. Mach. Learn. Res., 2010

On the relation between universality, characteristic kernels and RKHS embedding of measures.

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

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Non-parametric estimation of integral probability metrics.

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert R. G. Lanckriet

Proceedings of the IEEE International Symposium on Information Theory, 2010

2009

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

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf

CoRR, 2009

On the Convergence of the Concave-Convex Procedure.

Bharath K. Sriperumbudur, Gert R. G. Lanckriet

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions.

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

A Fast, Consistent Kernel Two-Sample Test.

Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Generalized Clustering via Kernel Embeddings.

Stefanie Jegelka, Arthur Gretton, Bernhard Schölkopf, Bharath K. Sriperumbudur, Ulrike von Luxburg

Proceedings of the KI 2009: Advances in Artificial Intelligence, 2009

2008

Characteristic Kernels on Groups and Semigroups.

Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Metric embedding for kernel classification rules.

Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G. Lanckriet

Proceedings of the Machine Learning, 2008

Injective Hilbert Space Embeddings of Probability Measures.

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf

Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007

Sparse eigen methods by D.C. programming.

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

Proceedings of the Machine Learning, 2007