—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Domain adaptation is a fundamental learning problem where one wishes to use labeled data from one or several source domains to learn a hypothesis performing well on a different, y...
Word meaning ambiguity has always been an important problem in information retrieval and extraction, as well as, text mining (documents clustering and classification). Knowledge di...
Henryk Rybinski, Marzena Kryszkiewicz, Grzegorz Pr...
— Mobile learning applications introduce a new degree of ubiquitousness in the learning process. There is a new generation of ICT-powered mobile learning experiences that exist i...