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20192026
most citedTrustworthy Dimensionality Reduction

2 citations · 4 across the 17 of their papers we have counts for

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7 papers · 1 filter

stat.ME2026

Nonparametric regression of spatio-temporal data using infinite-dimensional covariates

Subhrajyoty Roy, Soudeep Deb, Sayar Karmakar +1

In spatio-temporal analysis, we often record data at specific time intervals but with varying spatial locations between these timepoints. We propose a conditional model to analyze…

stat.ME2025

Robust Rank Estimation for Noisy Matrices

Subhrajyoty Roy, Abhik Ghosh, Ayanendranath Basu

Estimating the true rank of a noisy data matrix is a fundamental problem underlying techniques such as principal component analysis, matrix completion, etc. Existing rank estimatio…

stat.ME2024

Nonparametric quantile regression for spatio-temporal processes

Soudeep Deb, Claudia Neves, Subhrajyoty Roy

In this paper, we develop a new and effective approach to nonparametric quantile regression that accommodates ultrahigh-dimensional data arising from spatio-temporal processes. Thi…

stat.ME2024★ 2 cited

Trustworthy Dimensionality Reduction

Subhrajyoty Roy

Different unsupervised models for dimensionality reduction like PCA, LLE, Shannon's mapping, tSNE, UMAP, etc. work on different principles, hence, they are difficult to compare on…

stat.ME2023

Robust Principal Component Analysis using Density Power Divergence

Subhrajyoty Roy, Ayanendranath Basu, Abhik Ghosh

Principal component analysis (PCA) is a widely employed statistical tool used primarily for dimensionality reduction. However, it is known to be adversely affected by the presence…

stat.ME2022

Robust and Efficient Estimation in Ordinal Response Models using the Density Power Divergence

Arijit Pyne, Subhrajyoty Roy, Abhik Ghosh +1

In real life, we frequently come across data sets that involve some independent explanatory variable(s) generating a set of ordinal responses. These ordinal responses may correspon…

stat.ME2020

Rough-Fuzzy CPD: A Gradual Change Point Detection Algorithm

Ritwik Bhaduri, Subhrajyoty Roy, Sankar K. Pal

Changepoint detection is the problem of finding abrupt or gradual changes in time series data when the distribution of the time series changes significantly. There are many sophist…