We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...
Cross-domain learning methods have shown promising
results by leveraging labeled patterns from auxiliary domains
to learn a robust classifier for target domain, which
has a limi...
Dong Xu, Ivor Wai-Hung Tsang, Lixin Duan, Stephen ...
—In this paper, we study how a humanoid robot can learn affordance relations in his environment through its own interactions in an unsupervised way. Specifically, we developed a...
Baris Akgun, Nilgun Dag, Tahir Bilal, Ilkay Atil, ...
A graph-based prior is proposed for parametric semi-supervised classification. The prior utilizes both labelled and unlabelled data; it also integrates features from multiple view...
Balaji Krishnapuram, David Williams, Ya Xue, Alexa...
We propose a new multiple instance learning (MIL) algorithm to learn image categories. Unlike existing MIL algorithms, in which the individual instances in a bag are assumed to be...
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Tao Mei, Jin...