Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
Shaohua Kevin Zhou, Bogdan Georgescu, Dorin Comani...
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
Exploding amounts of multimedia data increasingly require automatic indexing and classification, e.g. training classifiers to produce high-level features, or semantic concepts, ch...
Wei Jiang, Eric Zavesky, Shih-Fu Chang, Alexander ...
Given a set of model graphs D and a query graph q, containment search aims to find all model graphs g D such that q contains g (q g). Due to the wide adoption of graph models, f...
Chen Chen, Xifeng Yan, Philip S. Yu, Jiawei Han, D...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...