The paper is an overview of a recently developed compilation data structure for graphical models, with specific application to constraint networks. The AND/OR Multi-Valued Decision...
This paper investigates the application of causal inference methodology for observational studies to software fault localization based on test outcomes and profiles. This methodo...
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
In the Steiner Network problem we are given a graph with edge-costs and connectivity requirements between node pairs , . The goal is to find a minimum-cost subgraph of that contain...
MohammadTaghi Hajiaghayi, Rohit Khandekar, Guy Kor...
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...