576 research outputs found

    Deep Extreme Multi-label Learning

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    Extreme multi-label learning (XML) or classification has been a practical and important problem since the boom of big data. The main challenge lies in the exponential label space which involves 2L2^L possible label sets especially when the label dimension LL is huge, e.g., in millions for Wikipedia labels. This paper is motivated to better explore the label space by originally establishing an explicit label graph. In the meanwhile, deep learning has been widely studied and used in various classification problems including multi-label classification, however it has not been properly introduced to XML, where the label space can be as large as in millions. In this paper, we propose a practical deep embedding method for extreme multi-label classification, which harvests the ideas of non-linear embedding and graph priors-based label space modeling simultaneously. Extensive experiments on public datasets for XML show that our method performs competitive against state-of-the-art result

    Joint Power Splitting and Secure Beamforming Design in the Wireless-powered Untrusted Relay Networks

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    In this work, we maximize the secrecy rate of the wireless-powered untrusted relay network by jointly designing power splitting (PS) ratio and relay beamforming with the proposed global optimal algorithm (GOA) and local optimal algorithm (LOA). Different from the literature, artificial noise (AN) sent by the destination not only degrades the channel condition of the eavesdropper to improve the secrecy rate, but also becomes a new source of energy powering the untrusted relay based on PS. Hence, it is of high economic benefits and efficiency to take advantage of AN compared with the literature. Simulation results show that LOA can achieve satisfactory secrecy rate performance compared with that of GOA, but with less computation time.Comment: Submitted to GlobeCom201

    The effect of cultivation methods on enhancing the methane oxidation capacity of ceramsite

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    AbstractInoculated with compost from methane oxidation habitats, the differences of methane oxidation capacity were compared and investigated after suspended-growth process and attached-growth process. The result showed that the ceramsite-compost matrix was formed in short time (3d) under the suspended growth condition and its methane oxidation capacity increased remarkably. The peak methane oxidation rate was 52.7g CH4·m-3·h-1 after suspended-growth process. However, the methane oxidation capacity of ceramsite was lower after attached-growth process with the peak methane oxidation rate of 13.5g CH4·m-3·h-1
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