10 citations · 47 across the 16 of their papers we have counts for
18 papers
Scalable Resampling in Massive Generalized Linear Models via Subsampled Residual Bootstrap
Indrila Ganguly, Srijan Sengupta, Sujit Ghosh
Residual bootstrap is a classical method for statistical inference in regression settings. With massive data sets becoming increasingly common, there is a demand for computationall…
Word Embeddings as Statistical Estimators
Neil Dey, Matthew Singer, Jonathan P. Williams +1
Word embeddings are a fundamental tool in natural language processing. Currently, word embedding methods are evaluated on the basis of empirical performance on benchmark data sets,…
Statistical Challenges in Online Controlled Experiments: A Review of A/B Testing Methodology
Nicholas Larsen, Jonathan Stallrich, Srijan Sengupta +3
The rise of internet-based services and products in the late 1990's brought about an unprecedented opportunity for online businesses to engage in large scale data-driven decision m…
Core-periphery structure in networks: a statistical exposition
Eric Yanchenko, Srijan Sengupta
Many real-world networks are theorized to have core-periphery structure consisting of a densely-connected core and a loosely-connected periphery. While this phenomenon has been ext…
A generalized hypothesis test for community structure in networks
Eric Yanchenko, Srijan Sengupta
Researchers theorize that many real-world networks exhibit community structure where within-community edges are more likely than between-community edges. While numerous methods exi…
Testing for the Network Small-World Property
Kartik Lovekar, Srijan Sengupta, Subhadeep Paul
Researchers have long observed that the ``small-world" property, which combines the concepts of high transitivity or clustering with a low average path length, is ubiquitous for ne…