111 citations · 318 across the 25 of their papers we have counts for
12 papers · 1 filter
Sparse Equisigned PCA: Algorithms and Performance Bounds in the Noisy Rank-1 Setting
Arvind Prasadan, Raj Rao Nadakuditi, Debashis Paul
Singular value decomposition (SVD) based principal component analysis (PCA) breaks down in the high-dimensional and limited sample size regime below a certain critical eigen-SNR th…
Spectral analysis of linear time series in moderately high dimensions
Lili Wang, Alexander Aue, Debashis Paul
This article is concerned with the spectral behavior of -dimensional linear processes in the moderately high-dimensional case when both dimensionality and sample size te…
Nonparametric estimation of dynamics of monotone trajectories
Debashis Paul, Jie Peng, Prabir Burman
We study a class of nonlinear nonparametric inverse problems. Specifically, we propose a nonparametric estimator of the dynamics of a monotonically increasing trajectory defined on…
High-dimensional genome-wide association study and misspecified mixed model analysis
Jiming Jiang, Cong Li, Debashis Paul +2
We study behavior of the restricted maximum likelihood (REML) estimator under a misspecified linear mixed model (LMM) that has received much attention in recent gnome-wide associat…
On the Marčenko-Pastur law for linear time series
Haoyang Liu, Alexander Aue, Debashis Paul
This paper is concerned with extensions of the classical Marčenko-Pastur law to time series. Specifically, -dimensional linear processes are considered which are built from inno…
Adaptation in a class of linear inverse problems
Iain M. Johnstone, Debashis Paul
We consider the linear inverse problem of estimating an unknown signal from noisy measurements on where the linear operator admits a wavelet-vaguelette decomposition (…