Recently, instead of selecting a single kernel, multiple kernel learning (MKL) has been proposed which uses a convex combination of kernels, where the weight of each kernel is opt...
Latent Dirichlet allocation (LDA) and other related topic models are increasingly popular tools for summarization and manifold discovery in discrete data. However, LDA does not ca...
Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...
Boosting methods are known not to usually overfit training data even as the size of the generated classifiers becomes large. Schapire et al. attempted to explain this phenomenon i...
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...