This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...
This paper points out some drawbacks and proposes some modifications to the conventional layer-by-layer BP algorithm. In particular, we present a new perspective to the learning ra...
Xu-Qin Li, Fei Han, Tat-Ming Lok, Michael R. Lyu, ...
We combine the strengths of Bayesian modeling and synchronous grammar in unsupervised learning of basic translation phrase pairs. The structured space of a synchronous grammar is ...
Hao Zhang, Chris Quirk, Robert C. Moore, Daniel Gi...
In this paper, we propose a framework for the design of learning activities, which follows the key idea of the “Learning-for-Use” model and adopts characteristics from the exp...
Agoritsa Gogoulou, Evangelia Gouli, Maria Grigoria...