Articles by Bharath K. Sriperumbudur

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Bharath K. Sriperumbudur

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Nyström Kernel Stein Discrepancy

3 days ago by Florian Kalinke and others

Machine Learning, Statistics Theory

Minimax Optimal Kernel Two-Sample Tests with Random Features

28 February 2025 by Soumya Mukherjee and Bharath Sriperumbudur

Statistics Theory, Machine Learning

Uniform Kernel Prober

11 February 2025 by Soumya Mukherjee and Bharath Sriperumbudur

Machine Learning, Statistics Theory

Spectral Regularized Kernel Goodness-of-Fit Tests

22 January 2025 by Omar Hagrass and others

Statistics Theory, Machine Learning

Optimal Rates for Functional Linear Regression with General Regularization

11 December 2024 by Naveen Gupta and others

Statistics Theory

(De)-regularized Maximum Mean Discrepancy Gradient Flow

23 September 2024 by Zonghao Chen and others

Machine Learning

(De)-regularized Maximum Mean Discrepancy Gradient Flow

23 September 2024 by Zonghao Chen and others

Machine Learning

Gradient Flows and Riemannian Structure in the Gromov-Wasserstein Geometry

16 July 2024 by Zhengxin Zhang and others

Analysis of PDEs, Optimization and Control

Regularized Stein Variational Gradient Flow

9 May 2024 by Ye He and others

Machine Learning, Numerical Analysis

Spectral Regularized Kernel Two-Sample Tests

1 May 2024 by Omar Hagrass and others

Statistics Theory, Machine Learning

Functional linear and single-index models: A unified approach via Gaussian Stein identity

26 March 2024 by Krishnakumar Balasubramanian and others

Statistics Theory

Convergence Analysis of Kernel Conjugate Gradient for Functional Linear Regression

4 October 2023 by Naveen Gupta and others

Statistics Theory

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

28 September 2023 by Zhengxin Zhang and others

Statistics Theory

Kernel ε-Greedy for Contextual Bandits

29 June 2023 by Sakshi Arya and Bharath Sriperumbudur

Machine Learning, Statistics Theory

Shrinkage Estimation of Higher Order Bochner Integrals

21 July 2022 by Saiteja Utpala and Bharath Sriperumbudur

Statistics Theory, Methodology

Shrinkage Estimation for the Diagonal Multivariate Exponential Families

1 July 2022 by Nikolas Siapoutis and others

Statistics Theory

Robust Topological Inference in the Presence of Outliers

3 June 2022 by Siddharth Vishwanath and others

Statistics Theory, Computational Geometry

Cycle Consistent Probability Divergences Across Different Spaces

22 November 2021 by Zhengxin Zhang and others

Machine Learning

On Distance and Kernel Measures of Conditional Independence

17 August 2020 by Tianhong Sheng and Bharath Sriperumbudur

Statistics Theory, Machine Learning

Gaussian Sketching yields a J-L Lemma in RKHS

12 March 2020 by Samory Kpotufe and Bharath Sriperumbudur

Machine Learning, Probability

Local minimax rates for closeness testing of discrete distributions

2 October 2019 by Joseph Lam-Weil and others

Statistics Theory, Information Theory

Adaptive Clustering Using Kernel Density Estimators

17 August 2019 by Ingo Steinwart and others

Machine Learning, Methodology

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

30 October 2018 by Motonobu Kanagawa and others

Numerical Analysis, Machine Learning

On Kernel Derivative Approximation with Random Fourier Features

21 October 2018 by Zoltan Szabo and Bharath Sriperumbudur

Machine Learning, Probability

Minimax Estimation of Quadratic Fourier Functionals

1 September 2018 by Shashank Singh and others

Statistics Theory, Information Theory

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

6 July 2018 by Motonobu Kanagawa and others

Machine Learning

Characteristic and Universal Tensor Product Kernels

13 May 2018 by Zoltan Szabo and Bharath Sriperumbudur

Machine Learning, Information Theory

Convergence guarantees for kernel-based quadrature rules in misspecified settings

28 October 2016 by Motonobu Kanagawa and others

Machine Learning

Optimal Rates for Random Fourier Features

4 November 2015 by Bharath Sriperumbudur and Zoltan Szabo

Statistics Theory, Machine Learning

On the Optimal Estimation of Probability Measures in Weak and Strong Topologies

1 July 2014 by Bharath Sriperumbudur

Statistics Theory, Probability

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Statistics Theory Machine Learning Information Theory Numerical Analysis Methodology Probability Analysis of PDEs Computation Computational Geometry Algebraic Topology Functional Analysis Applications