A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...
— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...
Topic models have been studied extensively in the context of monolingual corpora. Though there are some attempts to mine topical structure from cross-lingual corpora, they require ...
We analyze the application of ensemble learning to recommender systems on the Netflix Prize dataset. For our analysis we use a set of diverse state-of-the-art collaborative filt...
—Two probabilistic-based models, namely the Ensemble-Dependent Matrix model [1][3] and the Markov Random Field model [2], have been proposed to deal with faults in nanoscale syst...
Huifei Rao, Jie Chen, Changhong Yu, Woon Tiong Ang...