Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
Abstract. This paper proposes an expert peering system for information exchange. Our objective is to develop a real-time search engine for an online community where users can ask e...
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
We address the problem of efficiently gathering correlated data from a wireless sensor network, with the aim of designing algorithms with provable optimality guarantees, and unders...