3 citations · 4 across the 5 of their papers we have counts for
6 papers
Entropic Causal Inference: Graph Identifiability
Spencer Compton, Kristjan Greenewald, Dmitriy Katz +1
Entropic causal inference is a recent framework for learning the causal graph between two variables from observational data by finding the information-theoretically simplest struct…
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier
Spencer Compton, Dmitriy Katz, Benjamin Qi +2
Given a set of discrete probability distributions, the minimum entropy coupling is the minimum entropy joint distribution that has the input distributions as its marginals. This ha…
A Tighter Approximation Guarantee for Greedy Minimum Entropy Coupling
Spencer Compton
We examine the minimum entropy coupling problem, where one must find the minimum entropy variable that has a given set of distributions as its marginals.…
Entropic Causal Inference: Identifiability and Finite Sample Results
Spencer Compton, Murat Kocaoglu, Kristjan Greenewald +1
Entropic causal inference is a framework for inferring the causal direction between two categorical variables from observational data. The central assumption is that the amount of…
New Partitioning Techniques and Faster Algorithms for Approximate Interval Scheduling
Spencer Compton, Slobodan Mitrović, Ronitt Rubinfeld
Interval scheduling is a basic problem in the theory of algorithms and a classical task in combinatorial optimization. We develop a set of techniques for partitioning and grouping…
Edge Matching with Inequalities, Triangles, Unknown Shape, and Two Players
Jeffrey Bosboom, Charlotte Chen, Lily Chung +12
We analyze the computational complexity of several new variants of edge-matching puzzles. First we analyze inequality (instead of equality) constraints between adjacent tiles, prov…