22 citations · 86 across the 42 of their papers we have counts for
54 papers
Total Variation Distance for Product Distributions is -Complete
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel +3
We show that computing the total variation distance between two product distributions is -complete. This is in stark contrast with other distance measures such as Kul…
Distribution Learning Meets Graph Structure Sampling
Arnab Bhattacharyya, Sutanu Gayen, Philips George John +2
This work establishes a novel link between the problem of PAC-learning high-dimensional graphical models and the task of (efficient) counting and sampling of graph structures, usin…
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…
Active causal structure learning with advice
Davin Choo, Themis Gouleakis, Arnab Bhattacharyya
We introduce the problem of active causal structure learning with advice. In the typical well-studied setting, the learning algorithm is given the essential graph for the observati…
Near-Optimal Degree Testing for Bayes Nets
Vipul Arora, Arnab Bhattacharyya, Clément L. Canonne +1
This paper considers the problem of testing the maximum in-degree of the Bayes net underlying an unknown probability distribution over , given sample access to .…
Constraint Optimization over Semirings
A. Pavan, Kuldeep S. Meel, N. V. Vinodchandran +1
Interpretations of logical formulas over semirings have applications in various areas of computer science including logic, AI, databases, and security. Such interpretations provide…