4 citations · 5 across the 5 of their papers we have counts for
5 papers
Convergence properties of data augmentation algorithms for high-dimensional robit regression
Sourav Mukherjee, Kshitij Khare, Saptarshi Chakraborty
The logistic and probit link functions are the most common choices for regression models with a binary response. However, these choices are not robust to the presence of outliers/u…
Determining Standard Occupational Classification Codes from Job Descriptions in Immigration Petitions
Sourav Mukherjee, David Widmark, Vince DiMascio +1
Accurate specification of standard occupational classification (SOC) code is critical to the success of many U.S. work visa applications. Determination of correct SOC code relies o…
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…
Immigration Document Classification and Automated Response Generation
Sourav Mukherjee, Tim Oates, Vince DiMascio +4
In this paper, we consider the problem of organizing supporting documents vital to U.S. work visa petitions, as well as responding to Requests For Evidence (RFE) issued by the U.S.…
Graph Node Embeddings using Domain-Aware Biased Random Walks
Sourav Mukherjee, Tim Oates, Ryan Wright
The recent proliferation of publicly available graph-structured data has sparked an interest in machine learning algorithms for graph data. Since most traditional machine learning…