In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
— We study the problem of dynamic learning by a social network of agents. Each agent receives a signal about an underlying state and communicates with a subset of agents (his nei...
In this paper, we investigate multi-agent learning (MAL) in a multi-agent resource selection problem (MARS) in which a large group of agents are competing for common resources. Si...
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Online monitoring of a physical phenomenon over a geographical area is a popular application of sensor networks. Networks representative of this class of applications are typicall...