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Bharath K. Sriperumbudur
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2020 – today
- 2024
- [i27]Florian Kalinke, Zoltán Szabó, Bharath K. Sriperumbudur:
Nyström Kernel Stein Discrepancy. CoRR abs/2406.08401 (2024) - [i26]Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur:
(De)-regularized Maximum Mean Discrepancy Gradient Flow. CoRR abs/2409.14980 (2024) - 2023
- [j14]Tianhong Sheng, Bharath K. Sriperumbudur:
On Distance and Kernel Measures of Conditional Dependence. J. Mach. Learn. Res. 24: 7:1-7:16 (2023) - [j13]Ingo Steinwart, Bharath K. Sriperumbudur, Philipp Thomann:
Adaptive Clustering Using Kernel Density Estimators. J. Mach. Learn. Res. 24: 275:1-275:56 (2023) - [i25]Sakshi Arya, Bharath K. Sriperumbudur:
Kernel ε-Greedy for Contextual Bandits. CoRR abs/2306.17329 (2023) - 2022
- [j12]Nicholas Sterge, Bharath K. Sriperumbudur:
Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA. J. Mach. Learn. Res. 23: 337:1-337:32 (2022) - [c28]Zhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath K. Sriperumbudur:
Cycle Consistent Probability Divergences Across Different Spaces. AISTATS 2022: 7257-7285 - [i24]Siddharth Vishwanath, Bharath K. Sriperumbudur, Kenji Fukumizu, Satoshi Kuriki:
Robust Topological Inference in the Presence of Outliers. CoRR abs/2206.01795 (2022) - [i23]Ye He, Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Jianfeng Lu:
Regularized Stein Variational Gradient Flow. CoRR abs/2211.07861 (2022) - [i22]Omar Hagrass, Bharath K. Sriperumbudur, Bing Li:
Spectral Regularized Kernel Two-Sample Tests. CoRR abs/2212.09201 (2022) - 2021
- [i21]Nicholas Sterge, Bharath K. Sriperumbudur:
Statistical Optimality and Computational Efficiency of Nyström Kernel PCA. CoRR abs/2105.08875 (2021) - [i20]Zhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath K. Sriperumbudur:
Cycle Consistent Probability Divergences Across Different Spaces. CoRR abs/2111.11328 (2021) - 2020
- [j11]Motonobu Kanagawa
, Bharath K. Sriperumbudur, Kenji Fukumizu
Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings. Found. Comput. Math. 20(1): 155-194 (2020) - [c27]Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi:
Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling. AISTATS 2020: 3642-3652 - [c26]Samory Kpotufe, Bharath K. Sriperumbudur:
Gaussian Sketching yields a J-L Lemma in RKHS. AISTATS 2020: 3928-3937 - [c25]Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur:
Robust Persistence Diagrams using Reproducing Kernels. NeurIPS 2020 - [i19]Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur:
Robust Persistence Diagrams using Reproducing Kernels. CoRR abs/2006.10012 (2020)
2010 – 2019
- 2019
- [c24]Zoltán Szabó, Bharath K. Sriperumbudur:
On Kernel Derivative Approximation with Random Fourier Features. AISTATS 2019: 827-836 - [i18]Joseph Lam-Weil, Alexandra Carpentier, Bharath K. Sriperumbudur:
Local minimax rates for closeness testing of discrete distributions. CoRR abs/1902.01219 (2019) - [i17]Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi:
Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling. CoRR abs/1907.05226 (2019) - [i16]Samory Kpotufe, Bharath K. Sriperumbudur:
Kernel Sketching yields Kernel JL. CoRR abs/1908.05818 (2019) - 2018
- [i15]Shashank Singh, Bharath K. Sriperumbudur, Barnabás Póczos:
Minimax Estimation of Quadratic Fourier Functionals. CoRR abs/1803.11451 (2018) - [i14]Motonobu Kanagawa, Philipp Hennig, Dino Sejdinovic, Bharath K. Sriperumbudur:
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences. CoRR abs/1807.02582 (2018) - [i13]Zoltán Szabó, Bharath K. Sriperumbudur:
On Kernel Derivative Approximation with Random Fourier Features. CoRR abs/1810.05207 (2018) - 2017
- [j10]Krikamol Muandet
Kernel Mean Embedding of Distributions: A Review and Beyond. Found. Trends Mach. Learn. 10(1-2): 1-141 (2017) - [j9]Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Aapo Hyvärinen, Revant Kumar:
Density Estimation in Infinite Dimensional Exponential Families. J. Mach. Learn. Res. 18: 57:1-57:59 (2017) - [j8]Ilya O. Tolstikhin, Bharath K. Sriperumbudur, Krikamol Muandet:
Minimax Estimation of Kernel Mean Embeddings. J. Mach. Learn. Res. 18: 86:1-86:47 (2017) - [j7]Zoltán Szabó, Bharath K. Sriperumbudur:
Characteristic and Universal Tensor Product Kernels. J. Mach. Learn. Res. 18: 233:1-233:29 (2017) - [i12]Zoltán Szabó, Bharath K. Sriperumbudur:
Characteristic and Universal Tensor Product Kernels. CoRR abs/1708.08157 (2017) - [i11]Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu:
Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings. CoRR abs/1709.00147 (2017) - 2016
- [j6]Krikamol Muandet, Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf:
Kernel Mean Shrinkage Estimators. J. Mach. Learn. Res. 17: 48:1-48:41 (2016) - [j5]Zoltán Szabó, Bharath K. Sriperumbudur, Barnabás Póczos, Arthur Gretton:
Learning Theory for Distribution Regression. J. Mach. Learn. Res. 17: 152:1-152:40 (2016) - [c23]Ilya O. Tolstikhin, Bharath K. Sriperumbudur, Bernhard Schölkopf:
Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels. NIPS 2016: 1930-1938 - [c22]Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu:
Convergence guarantees for kernel-based quadrature rules in misspecified settings. NIPS 2016: 3288-3296 - [i10]Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf:
Kernel Mean Embedding of Distributions: A Review and Beyonds. CoRR abs/1605.09522 (2016) - 2015
- [c21]Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur:
Two-stage sampled learning theory on distributions. AISTATS 2015 - [c20]Bharath K. Sriperumbudur, Zoltán Szabó:
Optimal Rates for Random Fourier Features. NIPS 2015: 1144-1152 - [i9]Bharath K. Sriperumbudur, Zoltán Szabó:
Optimal Rates for Random Fourier Features. CoRR abs/1506.02155 (2015) - 2014
- [c19]Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf:
Kernel Mean Estimation and Stein Effect. ICML 2014: 10-18 - [c18]Krikamol Muandet, Bharath K. Sriperumbudur, Bernhard Schölkopf:
Kernel Mean Estimation via Spectral Filtering. NIPS 2014: 1-9 - [i8]Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur:
Consistent, Two-Stage Sampled Distribution Regression via Mean Embedding. CoRR abs/1402.1754 (2014) - [i7]Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf:
Kernel Mean Shrinkage Estimators. CoRR abs/1405.5505 (2014) - [i6]Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur:
Learning Theory for Distribution Regression. CoRR abs/1411.2066 (2014) - 2013
- [c17]Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Guy Lebanon:
Ultrahigh Dimensional Feature Screening via RKHS Embeddings. AISTATS 2013: 126-134 - [c16]Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish Karnick:
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions. ICML (3) 2013: 441-449 - [i5]Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish Karnick:
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions. CoRR abs/1305.2505 (2013) - [i4]Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf:
Kernel Mean Estimation and Stein's Effect. CoRR abs/1306.0842 (2013) - 2012
- [j4]Bharath K. Sriperumbudur, Gert R. G. Lanckriet:
A Proof of Convergence of the Concave-Convex Procedure Using Zangwill's Theory. Neural Comput. 24(6): 1391-1407 (2012) - [c15]Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu:
Hypothesis testing using pairwise distances and associated kernels. ICML 2012 - [c14]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: 1214-1222 - [c13]Bharath K. Sriperumbudur, Ingo Steinwart:
Consistency and Rates for Clustering with DBSCAN. AISTATS 2012: 1090-1098 - [i3]Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu:
Hypothesis testing using pairwise distances and associated kernels (with Appendix). CoRR abs/1205.0411 (2012) - [i2]Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu:
Equivalence of distance-based and RKHS-based statistics in hypothesis testing. CoRR abs/1207.6076 (2012) - 2011
- [j3]Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet:
Universality, Characteristic Kernels and RKHS Embedding of Measures. J. Mach. Learn. Res. 12: 2389-2410 (2011) - [j2]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): 3-39 (2011) - [c12]Bharath K. Sriperumbudur:
Mixture density estimation via Hilbert space embedding of measures. ISIT 2011: 1027-1030 - [c11]Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet:
Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint. NIPS 2011: 1773-1781 - 2010
- [j1]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: 1517-1561 (2010) - [c10]Bharath K. Sriperumbudur, Kenji Fukumizu
Non-parametric estimation of integral probability metrics. ISIT 2010: 1428-1432 - [c9]Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet:
On the relation between universality, characteristic kernels and RKHS embedding of measures. AISTATS 2010: 773-780
2000 – 2009
- 2009
- [c8]Stefanie Jegelka, Arthur Gretton
Generalized Clustering via Kernel Embeddings. KI 2009: 144-152 - [c7]Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur:
A Fast, Consistent Kernel Two-Sample Test. NIPS 2009: 673-681 - [c6]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: 1750-1758 - [c5]Bharath K. Sriperumbudur, Gert R. G. Lanckriet:
On the Convergence of the Concave-Convex Procedure. NIPS 2009: 1759-1767 - [i1]Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf:
A note on integral probability metrics and $\phi$-divergences. CoRR abs/0901.2698 (2009) - 2008
- [c4]Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf:
Injective Hilbert Space Embeddings of Probability Measures. COLT 2008: 111-122 - [c3]Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G. Lanckriet:
Metric embedding for kernel classification rules. ICML 2008: 1008-1015 - [c2]Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf:
Characteristic Kernels on Groups and Semigroups. NIPS 2008: 473-480 - 2007
- [c1]Bharath K. Sriperumbudur, David A. Torres, Gert R. G. Lanckriet:
Sparse eigen methods by D.C. programming. ICML 2007: 831-838
Coauthor Index
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