In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn relia...
Abstract. Adaptation is one of the most problematic steps in the design and development of Case Based Reasoning (CBR) systems, as it may require considerable domain knowledge and i...
The feedback loop for temporal prediction of traditional implementations of an MPEG-compliant video coder requires conversion of images from the spatial domain to the transform do...
We present a novel hierarchical prior structure for supervised transfer learning in named entity recognition, motivated by the common structure of feature spaces for this task acr...
Organizations involving multiple agents require adaptation mechanisms to guarantee robustness, especially in critical domains. This paper presents an organizational template to ai...