6 papers · 1 filter
Nonsense associations in Markov random fields with pairwise dependence
Sohom Bhattacharya, Rajarshi Mukherjee, Elizabeth Ogburn
Yule (1926) identified the issue of "nonsense correlations" in time series data, where dependence within each of two random vectors causes overdispersion -- i.e. variance inflation…
Inferences on Mixing Probabilities and Ranking in Mixed-Membership Models
Sohom Bhattacharya, Jianqing Fan, Jikai Hou
Network data is prevalent in numerous big data applications including economics and health networks where it is of prime importance to understand the latent structure of network. I…
Deep Neural Networks for Nonparametric Interaction Models with Diverging Dimension
Sohom Bhattacharya, Jianqing Fan, Debarghya Mukherjee
Deep neural networks have achieved tremendous success due to their representation power and adaptation to low-dimensional structures. Their potential for estimating structured regr…
PC Adjusted Testing for Low Dimensional Parameters
Sohom Bhattacharya, Rounak Dey, Rajarshi Mukherjee
In this paper, we investigate the impact of high-dimensional Principal Component (PC) adjustments on inferring the effects of variables on outcomes, with a focus on applications in…
Sharp Signal Detection Under Ferromagnetic Ising Models
Sohom Bhattacharya, Rajarshi Mukherjee, Gourab Ray
In this paper we study the effect of dependence on detecting a class of structured signals in Ferromagnetic Ising models. Natural examples of our class include Ising Models on latt…
Matrix completion with data-dependent missingness probabilities
Sohom Bhattacharya, Sourav Chatterjee
The problem of completing a large matrix with lots of missing entries has received widespread attention in the last couple of decades. Two popular approaches to the matrix completi…