3 citations · 3 across the 5 of their papers we have counts for
9 papers
Geometry of Rounding
Jason Vander Woude, Peter Dixon, A. Pavan +2
Rounding has proven to be a fundamental tool in theoretical computer science. By observing that rounding and partitioning of are equivalent, we introduce the followi…
Efficient inference of interventional distributions
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy +2
We consider the problem of efficiently inferring interventional distributions in a causal Bayesian network from a finite number of observations. Let be a causal model…
Model Counting meets F0 Estimation
A. Pavan, N. V. Vinodchandran, Arnab Bhattacharyya +1
Constraint satisfaction problems (CSP's) and data stream models are two powerful abstractions to capture a wide variety of problems arising in different domains of computer science…
Promise Problems Meet Pseudodeterminism
Peter Dixon, A. Pavan, N. V. Vinodchandran
The Acceptance Probability Estimation Problem (APEP) is to additively approximate the acceptance probability of a Boolean circuit. This problem admits a probabilistic approximation…
Testing Product Distributions: A Closer Look
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy +1
We study the problems of identity and closeness testing of -dimensional product distributions. Prior works by Canonne, Diakonikolas, Kane and Stewart (COLT 2017) and Daskalakis…
Near-Optimal Learning of Tree-Structured Distributions by Chow-Liu
Arnab Bhattacharyya, Sutanu Gayen, Eric Price +1
We provide finite sample guarantees for the classical Chow-Liu algorithm (IEEE Trans.~Inform.~Theory, 1968) to learn a tree-structured graphical model of a distribution. For a dist…