Despite substantial improvements in the last few years in software engineering and collaboration tools, coordination in large-scale software development continues to be problemati...
J. Alberto Espinosa, Robert E. Kraut, F. Javier Le...
Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
This paper explores the increasing the heterogeneity of an agent population to stabilize decentralized systems by adding bias terms to each agent's expected payoffs. Two appr...
System identification of plants with binary-valued output observations is of importance in understanding modeling capability and limitations for systems with limited sensor inform...
Spectral clustering algorithms have been shown to be more effective in finding clusters than some traditional algorithms such as k-means. However, spectral clustering suffers fro...