The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
Abstract. We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (S...
—Inspired by the success of the low-density parity-check (LDPC) codes in the field of error-control coding, in this paper we propose transforming the downlink multiuser multiple-...
Peer-to-peer grids are large-scale, dynamic environments where autonomous sites share computing resources. Producing and maintaining relevant and up-to-date resource information i...
Nazareno Andrade, Elizeu Santos-Neto, Francisco Vi...
Abstract— Categorizing visual elements is fundamentally important for autonomous mobile robots to get intelligence such as new object acquisition and topological place classific...