10 citations · 14 across the 11 of their papers we have counts for
6 papers · 1 filter
Entropy Equivalence Testing
Clément L. Canonne, Yash Pote, Jonathan Scarlett +1
We introduce the problem of \emph{entropy equivalence testing} for probability distributions, a relaxation of the well-studied closeness testing problem, where the distribution tes…
Instance Dependent Testing of Samplers using Interval Conditioning
Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote +2
Sampling algorithms play a pivotal role in probabilistic AI. However, verifying if a sampler program indeed samples from the claimed distribution is a notoriously hard problem. Pro…
A Distribution Testing Approach to Clustering Distributions
Gunjan Kumar, Yash Pote, Jonathan Scarlett
We study the following distribution clustering problem: Given a hidden partition of distributions into two groups, such that the distributions within each group are the same, a…
Testing Self-Reducible Samplers
Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote +2
Samplers are the backbone of the implementations of any randomised algorithm. Unfortunately, obtaining an efficient algorithm to test the correctness of samplers is very hard to fi…
Distance Estimation for High-Dimensional Discrete Distributions
Gunjan Kumar, Kuldeep S. Meel, Yash Pote
Given two distributions and over a high-dimensional domain , and a parameter , the goal of distance estimation is to determine t…
On Scalable Testing of Samplers
Yash Pote, Kuldeep S. Meel
In this paper we study the problem of testing of constrained samplers over high-dimensional distributions with guarantees. Samplers are increasingly used in a w…