Bharath K. Sriperumbudur

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 33

Top Topics

Kernel Density Estimation

Laplacian Eigenmaps

Learning Theory

Gaussian Processes

Top Venues

J. Mach. Learn. Res.

Publications

Florian Kalinke, Zoltán Szabó, Bharath K. Sriperumbudur
Nyström Kernel Stein Discrepancy. CoRR (2024)
Sakshi Arya, Bharath K. Sriperumbudur
Kernel ε-Greedy for Contextual Bandits. CoRR (2023)
Tianhong Sheng, Bharath K. Sriperumbudur
On Distance and Kernel Measures of Conditional Dependence. J. Mach. Learn. Res. 24 (2023)
Omar Hagrass, Bharath K. Sriperumbudur, Bing Li
Spectral Regularized Kernel Two-Sample Tests. CoRR (2022)
Siddharth Vishwanath, Bharath K. Sriperumbudur, Kenji Fukumizu, Satoshi Kuriki
Robust Topological Inference in the Presence of Outliers. CoRR (2022)
Ye He, Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Jianfeng Lu
Regularized Stein Variational Gradient Flow. CoRR (2022)
Zhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath K. Sriperumbudur
Cycle Consistent Probability Divergences Across Different Spaces. AISTATS (2022)
Nicholas Sterge, Bharath K. Sriperumbudur
Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA. J. Mach. Learn. Res. 23 (2022)
Zhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath K. Sriperumbudur
Cycle Consistent Probability Divergences Across Different Spaces. CoRR (2021)
Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings. Found. Comput. Math. 20 (1) (2020)
Samory Kpotufe, Bharath K. Sriperumbudur
Gaussian Sketching yields a J-L Lemma in RKHS. AISTATS (2020)
Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur
Robust Persistence Diagrams using Reproducing Kernels. NeurIPS (2020)
Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur
Robust Persistence Diagrams using Reproducing Kernels. CoRR (2020)
Samory Kpotufe, Bharath K. Sriperumbudur
Kernel Sketching yields Kernel JL. CoRR (2019)
Joseph Lam-Weil, Alexandra Carpentier, Bharath K. Sriperumbudur
Local minimax rates for closeness testing of discrete distributions. CoRR (2019)
Zoltán Szabó, Bharath K. Sriperumbudur
On Kernel Derivative Approximation with Random Fourier Features. AISTATS (2019)
Zoltán Szabó, Bharath K. Sriperumbudur
On Kernel Derivative Approximation with Random Fourier Features. CoRR (2018)
Motonobu Kanagawa, Philipp Hennig, Dino Sejdinovic, Bharath K. Sriperumbudur
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences. CoRR (2018)
Shashank Singh, Bharath K. Sriperumbudur, Barnabás Póczos
Minimax Estimation of Quadratic Fourier Functionals. CoRR (2018)
Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf
Kernel Mean Embedding of Distributions: A Review and Beyond. Found. Trends Mach. Learn. 10 (1-2) (2017)
Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings. CoRR (2017)
Zoltán Szabó, Bharath K. Sriperumbudur
Characteristic and Universal Tensor Product Kernels. J. Mach. Learn. Res. 18 (2017)
Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Aapo Hyvärinen, Revant Kumar
Density Estimation in Infinite Dimensional Exponential Families. J. Mach. Learn. Res. 18 (2017)
Ilya O. Tolstikhin, Bharath K. Sriperumbudur, Krikamol Muandet
Minimax Estimation of Kernel Mean Embeddings. J. Mach. Learn. Res. 18 (2017)
Zoltán Szabó, Bharath K. Sriperumbudur
Characteristic and Universal Tensor Product Kernels. CoRR (2017)
Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf
Kernel Mean Embedding of Distributions: A Review and Beyonds. CoRR (2016)
Zoltán Szabó, Bharath K. Sriperumbudur, Barnabás Póczos, Arthur Gretton
Learning Theory for Distribution Regression. J. Mach. Learn. Res. 17 (2016)
Krikamol Muandet, Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf
Kernel Mean Shrinkage Estimators. J. Mach. Learn. Res. 17 (2016)
Ilya O. Tolstikhin, Bharath K. Sriperumbudur, Bernhard Schölkopf
Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels. NIPS (2016)
Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
Convergence guarantees for kernel-based quadrature rules in misspecified settings. NIPS (2016)
Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur
Two-stage sampled learning theory on distributions. AISTATS (2015)
Bharath K. Sriperumbudur, Zoltán Szabó
Optimal Rates for Random Fourier Features. CoRR (2015)
Bharath K. Sriperumbudur, Zoltán Szabó
Optimal Rates for Random Fourier Features. NIPS (2015)
Krikamol Muandet, Bharath K. Sriperumbudur, Bernhard Schölkopf
Kernel Mean Estimation via Spectral Filtering. NIPS (2014)
Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur
Consistent, Two-Stage Sampled Distribution Regression via Mean Embedding. CoRR (2014)
Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
Kernel Mean Shrinkage Estimators. CoRR (2014)
Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur
Learning Theory for Distribution Regression. CoRR (2014)
Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
Kernel Mean Estimation and Stein Effect. ICML (2014)
Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
Kernel Mean Estimation and Stein's Effect. CoRR (2013)
Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish Karnick
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions CoRR (2013)
Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish Karnick
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions. ICML (3) (2013)
Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Guy Lebanon
Ultrahigh Dimensional Feature Screening via RKHS Embeddings. AISTATS (2013)
Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu
Optimal kernel choice for large-scale two-sample tests. NIPS (2012)
Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu
Hypothesis testing using pairwise distances and associated kernels (with Appendix) CoRR (2012)
Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu
Hypothesis testing using pairwise distances and associated kernels. ICML (2012)
Bharath K. Sriperumbudur, Ingo Steinwart
Consistency and Rates for Clustering with DBSCAN. AISTATS (2012)
Bharath K. Sriperumbudur, Gert R. G. Lanckriet
A Proof of Convergence of the Concave-Convex Procedure Using Zangwill's Theory. Neural Comput. 24 (6) (2012)
Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu
Equivalence of distance-based and RKHS-based statistics in hypothesis testing CoRR (2012)
Bharath K. Sriperumbudur, David A. Torres, Gert R. G. Lanckriet
A majorization-minimization approach to the sparse generalized eigenvalue problem. Mach. Learn. 85 (1-2) (2011)
Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet
Universality, Characteristic Kernels and RKHS Embedding of Measures. J. Mach. Learn. Res. 12 (2011)
Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet
Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint. NIPS (2011)
Bharath K. Sriperumbudur
Mixture density estimation via Hilbert space embedding of measures. ISIT (2011)
Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet
On the relation between universality, characteristic kernels and RKHS embedding of measures. AISTATS (2010)
Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet
Hilbert Space Embeddings and Metrics on Probability Measures. J. Mach. Learn. Res. 11 (2010)
Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert R. G. Lanckriet
Non-parametric estimation of integral probability metrics. ISIT (2010)
Bharath K. Sriperumbudur, Gert R. G. Lanckriet
On the Convergence of the Concave-Convex Procedure. NIPS (2009)
Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, Bernhard Schölkopf
Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions. NIPS (2009)
Stefanie Jegelka, Arthur Gretton, Bernhard Schölkopf, Bharath K. Sriperumbudur, Ulrike von Luxburg
Generalized Clustering via Kernel Embeddings. KI (2009)
Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf
A note on integral probability metrics and $\phi$-divergences CoRR (2009)
Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur
A Fast, Consistent Kernel Two-Sample Test. NIPS (2009)
Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
Characteristic Kernels on Groups and Semigroups. NIPS (2008)
Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf
Injective Hilbert Space Embeddings of Probability Measures. COLT (2008)
Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G. Lanckriet
Metric embedding for kernel classification rules. ICML (2008)
Bharath K. Sriperumbudur, David A. Torres, Gert R. G. Lanckriet
Sparse eigen methods by D.C. programming. ICML (2007)