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Learning to hash has attracted broad research interests in recent computer vision and machine learning studies, due to its ability to accomplish efficient approximate nearest neighbor search. However, the closely related task, maximum inner product search (MIPS), has rarely been studied in this literature. To facilitate the MIPS study, in this paper, we introduce a general binary coding framework...
Learning based hashing has become increasingly popular because of its high efficiency in handling the large scale image retrieval. Preserving the pairwise similarities of data points in the Hamming space is critical in state-of-the-art hashing techniques. However, most previous methods ignore to capture the local geometric structure residing on original data, which is essential for similarity search...
This paper is concerned with the transmission strategies and relay selection for decode-and-forward parallel relay networks (PRNs) based on superposition coding. Our focus is on the minimization of the aggregate transmission power that supports a given transmission rate. In this paper, two transmission strategies are investigated, i.e., an optimal- cooperation (OC) strategy requiring strict synchronization...
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