108 citations · 108 across the 4 of their papers we have counts for
4 papers
Causal inference under interference: computational barriers and algorithmic solutions
Sohom Bhattacharya, Subhabrata Sen
We study causal effect estimation under interference from network data. We work under the chain-graph formulation pioneered in Tchetgen Tchetgen et. al (2021). Our first result sho…
Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models
Taj Jones-McCormick, Aukosh Jagannath, Subhabrata Sen
Unsupervised pre-training and transfer learning are commonly used techniques to initialize training algorithms for neural networks, particularly in settings with limited labeled da…
Causal effect estimation under network interference with mean-field methods
Sohom Bhattacharya, Subhabrata Sen
We study causal effect estimation from observational data under interference. The interference pattern is captured by an observed network. We adopt the chain graph framework of Tch…
Extremal Cuts of Sparse Random Graphs
Amir Dembo, Andrea Montanari, Subhabrata Sen
For Erdős-Rényi random graphs with average degree , and uniformly random -regular graph on vertices, we prove that with high probability the size of both the Max-Cut and…