We consider the problem of learning mixtures of arbitrary symmetric distributions. We formulate sufficient separation conditions and present a learning algorithm with provable gua...
Anirban Dasgupta, John E. Hopcroft, Jon M. Kleinbe...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
In this paper, we propose a distributed learning strategy in wireless sensor networks. Taking advantage of recent developments on kernel-based machine learning, we consider a new ...
Abstract. Coordination is an essential technique in cooperative, distributed multiagent systems. However, sophisticated coordination strategies are not always cost-effective in all...
: Growing importance of distributed data mining techniques has recently attracted attention of researchers in multiagent domain. Several agent-based application have been already c...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek, S...