Optimized deep learning for Indian Classical Dance Classification a novel application based on a refined version of chameleon swarm algorithm. [PDF]
Zhu D, Sun J, Lu Y, Bastani C.
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Markov Determinantal Point Process for Dynamic Random Sets
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
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Sampled-data control under time-varying delays: a robust approach for high-renewable smart grids. [PDF]
Hassan M.
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Double reinforcement learning for cluster synchronization of Boolean control networks under denial of service attacks. [PDF]
Deng W, Huang C, Shuai Q.
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Resolving discrepancies between chimeric and multiplicative measures of higher-order epistasis. [PDF]
Chitra U, Arnold B, Raphael BJ.
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A Study on Distributed Multi-Sensor Fusion for Nonlinear Systems Under Non-Overlapping Fields of View. [PDF]
Wang L +5 more
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Bayesian Prediction of Event Times Using Mixture Model for Blinded Randomized Controlled Trials. [PDF]
Fu J +5 more
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