12 citations · 19 across the 17 of their papers we have counts for
4 papers · 1 filter
High Dimensional Logistic Regression Under Network Dependence
Somabha Mukherjee, Ziang Niu, Sagnik Halder +2
Logistic regression is key method for modeling the probability of a binary outcome based on a collection of covariates. However, the classical formulation of logistic regression re…
Limit theorems for dependent combinatorial data, with applications in statistical inference
Somabha Mukherjee
The Ising model is a celebrated example of a Markov random field, introduced in statistical physics to model ferromagnetism. This is a discrete exponential family with binary outco…
Efficient Estimation in Tensor Ising Models
Somabha Mukherjee, Jaesung Son, Swarnadip Ghosh +1
The tensor Ising model is a discrete exponential family used for modeling binary data on networks with not just pairwise, but higher-order dependencies. A particularly important cl…
Feature Selection in High-dimensional Spaces Using Graph-Based Methods
Swarnadip Ghosh, Somabha Mukherjee, Divyansh Agarwal +3
High-dimensional feature selection is a central problem in a variety of application domains such as machine learning, image analysis, and genomics. In this paper, we propose graph-…