16 citations · 42 across the 21 of their papers we have counts for
9 papers · 1 filter
Estimating Size of the Union of Sets in Streaming Model
Kuldeep S. Meel, N. V. Vinodchandran, Sourav Chakraborty
We study estimating the size of the union of sets , where each is presented implicitly and arrives in a stream. We introduce Delphic sets, a class of…
Fast Rational Search via Stern-Brocot Tree
Connor Weyers, N. V. Vinodchandran
We revisit the problem of rational search: given an unknown rational number with , the goal is to identify using comparison queries of the…
Total Variation Distance Meets Probabilistic Inference
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel +3
In this paper, we establish a novel connection between total variation (TV) distance estimation and probabilistic inference. In particular, we present an efficient, structure-prese…
On Approximating Total Variation Distance
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel +3
Total variation distance (TV distance) is a fundamental notion of distance between probability distributions. In this work, we introduce and study the problem of computing the TV d…
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…
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…
Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel +1
We design efficient distance approximation algorithms for several classes of structured high-dimensional distributions. Specifically, we show algorithms for the following problems:…