Recently, spectral kernels have attracted wide attention in complex dynamic environments. These advanced kernels mainly focus on breaking through the crucial limitation on locality, that is, the stationarity and the monotonicity. But actually, owing to the inefficiency of shallow models in computational elements, they are more likely unable to accurately reveal dynamic and potential variations. In this paper, we propose a novel deep spectral kernel network (DSKN) to naturally integrate non-stationary and non-monotonic spectral kernels into elegant deep architectures in an interpretable way, which can be further generalized to cover most kernels. Concretely, we firstly deal with the general form of spectral kernels by the inverse Fourier transform. Secondly, DSKN is constructed by embedding the preeminent spectral kernels into each layer to boost the efficiency in computational elements, which can effectively reveal the dynamic input-dependent characteristics and potential long-range correlations by compactly representing complex advanced concepts. Thirdly, detailed analyses of DSKN are presented. Owing to its universality, we propose a unified spectral transform technique to flexibly extend and reasonably initialize domain-related DSKN. Furthermore, the representer theorem of DSKN is given. Systematical experiments demonstrate the superiority of DSKN compared to state-of-the-art relevant algorithms on varieties of standard real-world tasks.
Abstract-The development of collaborative multimedia applications today follows a vertical development approach, which is a major inhibitor that drives up the cost of development and slows down the pace of innovation of new generations of collaborative applications. In this paper, we propose a network communication broker (NCB) that provides a unified higherlevel abstraction that encapsulates the complexity of networklevel communication control and media delivery for the class of multimedia collaborative applications. NCB expedites the development of next-generation applications with diverse communication logics. Furthermore, NCB-based applications can be easily ported to new network environments. In addition, the self-managing design of NCB supports dynamic adaptation in response to changes in network conditions and user requirements.
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