In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Recent work has demonstrated that using a carefully designed dictionary instead of a predefined one, can improve the sparsity in jointly representing a class of signals. This has m...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
Recent work has demonstrated that using a carefully designed sensing matrix rather than a random one, can improve the performance of compressed sensing. In particular, a welldesign...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn fea...
Shuang-Hong Yang, Hongyuan Zha, Shaohua Kevin Zhou...
Several novel and particularly successful object and object category detection and recognition methods based on image features, local descriptions of object appearance, have recent...
Jarmo Ilonen, Joni-Kristian Kamarainen, Pekka Paal...