56 citations · 238 across the 48 of their papers we have counts for
9 papers · 1 filter
MixCIT: A Kernel Based Local-Polynomial Debiased Test for Conditional Independence on Mixed-Type Data
Mengxiao Gao, Kyra Gan, Promit Ghosal
Conditional independence testing (CIT) is fundamental to modern statistical inference in areas related to causal discovery and variable selection. While marginal independence is re…
Distribution-free Measures of Association based on Optimal Transport
Nabarun Deb, Promit Ghosal, Bodhisattva Sen
In this paper we propose and study a class of nonparametric, yet interpretable measures of association between two random vectors and taking values in an…
Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
Sayan Banerjee, Krishnakumar Balasubramanian, Promit Ghosal
We provide finite-particle convergence rates for the Stein Variational Gradient Descent (SVGD) algorithm in the Kernelized Stein Discrepancy () and Wasserstein-2 metr…
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent
Tianle Liu, Promit Ghosal, Krishnakumar Balasubramanian +1
Stein Variational Gradient Descent (SVGD) is a nonparametric particle-based deterministic sampling algorithm. Despite its wide usage, understanding the theoretical properties of SV…
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
Bhavya Agrawalla, Krishnakumar Balasubramanian, Promit Ghosal
Stochastic gradient descent (SGD) has emerged as the quintessential method in a data scientist's toolbox. Using SGD for high-stakes applications requires, however, careful quantifi…
Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections
Nabarun Deb, Promit Ghosal, Bodhisattva Sen
Optimal transport maps between two probability distributions and on have found extensive applications in both machine learning and statistics. In practice, t…
Measuring Association on Topological Spaces Using Kernels and Geometric Graphs
Nabarun Deb, Promit Ghosal, Bodhisattva Sen
In this paper we propose and study a class of simple, nonparametric, yet interpretable measures of association between two random variables and taking values in general top…
Multivariate Ranks and Quantiles using Optimal Transport: Consistency, Rates, and Nonparametric Testing
Promit Ghosal, Bodhisattva Sen
In this paper we study multivariate ranks and quantiles, defined using the theory of optimal transport, and build on the work of Chernozhukov et al.(2017) and Hallin et al.(2021).…
Joint estimation of parameters in Ising model
Promit Ghosal, Sumit Mukherjee
We study joint estimation of the inverse temperature and magnetization parameters of an Ising model with a non-negative coupling matrix of size , given one…