In this paper we introduce a new sparseness inducing prior which does not involve any (hyper)parameters that need to be adjusted or estimated. Although other applications are poss...
Developing a learning design using IMS Learning Design (LD) is difficult for average practitioners because a high overhead of pedagogical knowledge and technical knowledge is requi...
Yongwu Miao, Tim Sodhi, Francis Brouns, Peter B. S...
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
In this paper, we present a simple yet efficient automatic system to translate biomedical terms. It mainly relies on a machine learning approach able to infer rewriting rules from...