In this paper we propose interaction-driven Markov games (IDMGs), a new model for multiagent decision making under uncertainty. IDMGs aim at describing multiagent decision problem...
As the ability to produce a large number of small, simple robotic agents improves, it becomes essential to control the behavior of these agents in such a way that the sum of their...
Given a connected graph G and a failure probability pe for each edge e in G, the reliability of G is the probability that G remains connected when each edge e is removed independe...
Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
We introduce a multi-stage ensemble framework, ErrorDriven Generalist+Expert or Edge, for improved classification on large-scale text categorization problems. Edge first trains a ...