We present a framework for an automated generation of exact search tree algorithms for NP-hard problems. The purpose of our approach is two-fold--rapid development and improved up...
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
We present a new matrix formulation of the face hypercube embedding problem that motivates the design of an efficient search strategy to find an encoding that satisfies all fac...
Evguenii I. Goldberg, Tiziano Villa, Robert K. Bra...
Abstract— This paper describes a novel algorithm for autonomous and incremental learning of motion pattern primitives by observation of human motion. Human motion patterns are ed...
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...