We show how models for prediction with expert advice can be defined concisely and clearly using hidden Markov models (HMMs); standard HMM algorithms can then be used to efficientl...
This paper presents a novel and notable swarm approach to evolve an optimal set of weights and architecture of a neural network for classification in data mining. In a distributed ...
The decentralized control scheme for routing in current IP networks has been questioned, and a centralized control scheme has been proposed. In this paper, we compare the convergen...
We revisit the peer selection problem of finding the most nearby peer from an initiating node. The metrics to assess the closeness between peers are hopcount and delay, respectivel...
We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...