In this paper, an unsupervised learning algorithm, neighborhood linear embedding (NLE), is proposed to discover the intrinsic structures such as neighborhood relationships, global ...
Shuzhi Sam Ge, Feng Guan, Yaozhang Pan, Ai Poh Loh
In this paper, we investigate how modeling content structure can benefit text analysis applications such as extractive summarization and sentiment analysis. This follows the lingu...
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
There is an obvious need for improving the performance and accuracy of a Bayesian network as new data is observed. Because of errors in model construction and changes in the dynam...
Abstract. The nearest neighbor and the perceptron algorithms are intuitively motivated by the aims to exploit the “cluster” and “linear separation” structure of the data to...