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05/19/2021
Statistical Optimality and Computational Efficiency of Nyström Kernel PCA
Kernel methods provide an elegant framework for developing nonlinear lea...
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01/01/2020
Statistical Invariance of Betti Numbers in the Thermodynamic Regime
Topological Data Analysis (TDA) has become a promising tool to uncover l...
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07/11/2019
Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling
In this paper, we propose and study a Nyström based approach to efficien...
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02/19/2019
Optimal Function-on-Scalar Regression over Complex Domains
In this work we consider the problem of estimating function-on-scalar re...
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06/20/2017
Statistical Consistency of Kernel PCA with Random Features
Kernel methods are powerful learning methodologies that provide a simple...
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05/31/2016
Kernel Mean Embedding of Distributions: A Review and Beyond
A Hilbert space embedding of a distribution---in short, a kernel mean em...
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11/08/2014
Learning Theory for Distribution Regression
We focus on the distribution regression problem: regressing to vector-va...
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11/04/2014
Kernel Mean Estimation via Spectral Filtering
The problem of estimating the kernel mean in a reproducing kernel Hilber...
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05/21/2014
Kernel Mean Shrinkage Estimators
A mean function in a reproducing kernel Hilbert space (RKHS), or a kerne...
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02/07/2014
Two-stage Sampled Learning Theory on Distributions
We focus on the distribution regression problem: regressing to a real-va...
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12/12/2013
Density Estimation in Infinite Dimensional Exponential Families
In this paper, we consider an infinite dimensional exponential family, P...
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06/04/2013
Kernel Mean Estimation and Stein's Effect
A mean function in reproducing kernel Hilbert space, or a kernel mean, i...
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07/25/2012
Equivalence of distance-based and RKHS-based statistics in hypothesis testing
We provide a unifying framework linking two classes of statistics used i...
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05/02/2012