Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Using a ground truth extracted from the Wikipedia, and a ground truth created through manual assessment, we show that the apparent performance advantage seen in machine learning a...
Tree-structured probabilistic models admit simple, fast inference. However, they are not well suited to phenomena such as occlusion, where multiple components of an object may dis...
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Mining frequent patterns is a general and important issue in data mining. Complex and unstructured (or semi-structured) datasets have appeared in major data mining applications, i...
Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhi...