Bharath K. Sriperumbudur

77 papers A* 6A 9B 2Misc 1Journal 48Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Kernel Single-Index Bandits: Estimation, Inference, and Learning. CoRR Sakshi Arya, Satarupa Bhattacharjee, Bharath K. Sriperumbudur
2025	J	`jnl`	(De)-regularized Maximum Mean Discrepancy Gradient Flow. J. Mach. Learn. Res. Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur
2025	J	`jnl`	Gaussian Processes and Reproducing Kernels: Connections and Equivalences. CoRR Motonobu Kanagawa, Philipp Hennig, Dino Sejdinovic, Bharath K. Sriperumbudur
2025	J	`jnl`	Minimax Optimal Kernel Two-Sample Tests with Random Features. CoRR Soumya Mukherjee, Bharath K. Sriperumbudur
2025	A	`conf`	Nyström Kernel Stein Discrepancy. AISTATS Florian Kalinke, Zoltán Szabó, Bharath K. Sriperumbudur
2025	J	`jnl`	Regularized Stein Variational Gradient Flow. Found. Comput. Math. Ye He, Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Jianfeng Lu
2025	J	`jnl`	Uniform Kernel Prober. CoRR Soumya Mukherjee, Bharath K. Sriperumbudur
2024	J	`jnl`	(De)-regularized Maximum Mean Discrepancy Gradient Flow. CoRR Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur
2024	J	`jnl`	Nyström Kernel Stein Discrepancy. CoRR Florian Kalinke, Zoltán Szabó, Bharath K. Sriperumbudur
2024	J	`jnl`	Spectral Regularized Kernel Goodness-of-Fit Tests. J. Mach. Learn. Res. Omar Hagrass, Bharath K. Sriperumbudur, Bing Li
2023	J	`jnl`	Adaptive Clustering Using Kernel Density Estimators. J. Mach. Learn. Res. Ingo Steinwart, Bharath K. Sriperumbudur, Philipp Thomann
2023	J	`jnl`	Kernel ε-Greedy for Contextual Bandits. CoRR Sakshi Arya, Bharath K. Sriperumbudur
2023	J	`jnl`	On Distance and Kernel Measures of Conditional Dependence. J. Mach. Learn. Res. Tianhong Sheng, Bharath K. Sriperumbudur
2022	A	`conf`	Cycle Consistent Probability Divergences Across Different Spaces. AISTATS Zhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath K. Sriperumbudur
2022	J	`jnl`	Regularized Stein Variational Gradient Flow. CoRR Ye He, Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Jianfeng Lu
2022	J	`jnl`	Robust Topological Inference in the Presence of Outliers. CoRR Siddharth Vishwanath, Bharath K. Sriperumbudur, Kenji Fukumizu, Satoshi Kuriki
2022	J	`jnl`	Spectral Regularized Kernel Two-Sample Tests. CoRR Omar Hagrass, Bharath K. Sriperumbudur, Bing Li
2022	J	`jnl`	Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA. J. Mach. Learn. Res. Nicholas Sterge, Bharath K. Sriperumbudur
2021	J	`jnl`	Cycle Consistent Probability Divergences Across Different Spaces. CoRR Zhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath K. Sriperumbudur
2021	J	`jnl`	Statistical Optimality and Computational Efficiency of Nyström Kernel PCA. CoRR Nicholas Sterge, Bharath K. Sriperumbudur
2020	J	`jnl`	Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings. Found. Comput. Math. Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
2020	A	`conf`	Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling. AISTATS Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi
2020	A	`conf`	Gaussian Sketching yields a J-L Lemma in RKHS. AISTATS Samory Kpotufe, Bharath K. Sriperumbudur
2020	A*	`conf`	Robust Persistence Diagrams using Reproducing Kernels. NeurIPS Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur
2020	J	`jnl`	Robust Persistence Diagrams using Reproducing Kernels. CoRR Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur
2019	J	`jnl`	Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling. CoRR Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi
2019	J	`jnl`	Kernel Sketching yields Kernel JL. CoRR Samory Kpotufe, Bharath K. Sriperumbudur
2019	J	`jnl`	Local minimax rates for closeness testing of discrete distributions. CoRR Joseph Lam-Weil, Alexandra Carpentier, Bharath K. Sriperumbudur
2019	A	`conf`	On Kernel Derivative Approximation with Random Fourier Features. AISTATS Zoltán Szabó, Bharath K. Sriperumbudur
2018	J	`jnl`	Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences. CoRR Motonobu Kanagawa, Philipp Hennig, Dino Sejdinovic, Bharath K. Sriperumbudur
2018	J	`jnl`	Minimax Estimation of Quadratic Fourier Functionals. CoRR Shashank Singh, Bharath K. Sriperumbudur, Barnabás Póczos
2018	J	`jnl`	On Kernel Derivative Approximation with Random Fourier Features. CoRR Zoltán Szabó, Bharath K. Sriperumbudur
2017	J	`jnl`	Characteristic and Universal Tensor Product Kernels. CoRR Zoltán Szabó, Bharath K. Sriperumbudur
2017	J	`jnl`	Characteristic and Universal Tensor Product Kernels. J. Mach. Learn. Res. Zoltán Szabó, Bharath K. Sriperumbudur
2017	J	`jnl`	Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings. CoRR Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
2017	J	`jnl`	Density Estimation in Infinite Dimensional Exponential Families. J. Mach. Learn. Res. Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Aapo Hyvärinen, Revant Kumar
2017	J	`jnl`	Kernel Mean Embedding of Distributions: A Review and Beyond. Found. Trends Mach. Learn. Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf
2017	J	`jnl`	Minimax Estimation of Kernel Mean Embeddings. J. Mach. Learn. Res. Ilya O. Tolstikhin, Bharath K. Sriperumbudur, Krikamol Muandet
2016	—	`conf`	Convergence guarantees for kernel-based quadrature rules in misspecified settings. NIPS Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
2016	J	`jnl`	Kernel Mean Embedding of Distributions: A Review and Beyonds. CoRR Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf
2016	J	`jnl`	Kernel Mean Shrinkage Estimators. J. Mach. Learn. Res. Krikamol Muandet, Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf
2016	J	`jnl`	Learning Theory for Distribution Regression. J. Mach. Learn. Res. Zoltán Szabó, Bharath K. Sriperumbudur, Barnabás Póczos, Arthur Gretton
2016	—	`conf`	Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels. NIPS Ilya O. Tolstikhin, Bharath K. Sriperumbudur, Bernhard Schölkopf
2015	—	`conf`	Optimal Rates for Random Fourier Features. NIPS Bharath K. Sriperumbudur, Zoltán Szabó
2015	J	`jnl`	Optimal Rates for Random Fourier Features. CoRR Bharath K. Sriperumbudur, Zoltán Szabó
2015	A	`conf`	Two-stage sampled learning theory on distributions. AISTATS Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur
2014	J	`jnl`	Consistent, Two-Stage Sampled Distribution Regression via Mean Embedding. CoRR Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur
2014	A*	`conf`	Kernel Mean Estimation and Stein Effect. ICML Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2014	—	`conf`	Kernel Mean Estimation via Spectral Filtering. NIPS Krikamol Muandet, Bharath K. Sriperumbudur, Bernhard Schölkopf
2014	J	`jnl`	Kernel Mean Shrinkage Estimators. CoRR Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2014	J	`jnl`	Learning Theory for Distribution Regression. CoRR Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur
2013	J	`jnl`	Kernel Mean Estimation and Stein's Effect. CoRR Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2013	J	`jnl`	On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions CoRR Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish Karnick
2013	—	`conf`	On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions. ICML (3) Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish Karnick
2013	A	`conf`	Ultrahigh Dimensional Feature Screening via RKHS Embeddings. AISTATS Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Guy Lebanon
2012	J	`jnl`	A Proof of Convergence of the Concave-Convex Procedure Using Zangwill's Theory. Neural Comput. Bharath K. Sriperumbudur, Gert R. G. Lanckriet
2012	A	`conf`	Consistency and Rates for Clustering with DBSCAN. AISTATS Bharath K. Sriperumbudur, Ingo Steinwart
2012	J	`jnl`	Equivalence of distance-based and RKHS-based statistics in hypothesis testing CoRR Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu
2012	J	`jnl`	Hypothesis testing using pairwise distances and associated kernels (with Appendix) CoRR Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu
2012	A*	`conf`	Hypothesis testing using pairwise distances and associated kernels. ICML Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu
2012	—	`conf`	Optimal kernel choice for large-scale two-sample tests. NIPS Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu
2011	J	`jnl`	A majorization-minimization approach to the sparse generalized eigenvalue problem. Mach. Learn. Bharath K. Sriperumbudur, David A. Torres, Gert R. G. Lanckriet
2011	—	`conf`	Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint. NIPS Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet
2011	B	`conf`	Mixture density estimation via Hilbert space embedding of measures. ISIT Bharath K. Sriperumbudur
2011	J	`jnl`	Universality, Characteristic Kernels and RKHS Embedding of Measures. J. Mach. Learn. Res. Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet
2010	J	`jnl`	Hilbert Space Embeddings and Metrics on Probability Measures. J. Mach. Learn. Res. Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet
2010	B	`conf`	Non-parametric estimation of integral probability metrics. ISIT Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert R. G. Lanckriet
2010	A	`conf`	On the relation between universality, characteristic kernels and RKHS embedding of measures. AISTATS Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet
2009	—	`conf`	A Fast, Consistent Kernel Two-Sample Test. NIPS Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur
2009	J	`jnl`	A note on integral probability metrics and $\phi$-divergences CoRR Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf
2009	Misc	`conf`	Generalized Clustering via Kernel Embeddings. KI Stefanie Jegelka, Arthur Gretton, Bernhard Schölkopf, Bharath K. Sriperumbudur, Ulrike von Luxburg
2009	—	`conf`	Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions. NIPS Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, Bernhard Schölkopf
2009	—	`conf`	On the Convergence of the Concave-Convex Procedure. NIPS Bharath K. Sriperumbudur, Gert R. G. Lanckriet
2008	—	`conf`	Characteristic Kernels on Groups and Semigroups. NIPS Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2008	A*	`conf`	Injective Hilbert Space Embeddings of Probability Measures. COLT Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf
2008	A*	`conf`	Metric embedding for kernel classification rules. ICML Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G. Lanckriet
2007	A*	`conf`	Sparse eigen methods by D.C. programming. ICML Bharath K. Sriperumbudur, David A. Torres, Gert R. G. Lanckriet