To jointly tackle the challenges of data and node heterogeneity in decentralized learning, we propose a distributed strong lottery ticket hypothesis (DSLTH), based on which a communication-efficient personalized learn...
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Fault diagnosis and isolation is important for industrial system. In this paper, a kernel canonical variate analysis(KCVA) is proposed for fault isolation. KCVA is originally used as a data dimension reduction techniq...
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Fault diagnosis and isolation is important for industrial system. In this paper, a kernel canonical variate analysis(KCVA) is proposed for fault isolation. KCVA is originally used as a data dimension reduction technique which can account for nonlinearity and correlations in the industrial dynamical process data. But there are some difficulties using KCVA in the construction of the contribution for the fault isolation. On the one hand, it is difficult to compute the contributions of individual variables because it is scarcely possible to find an inverse mapping from the feature space to the original space. On the other hand, a smearing effect is hardly avoided. To solve the problem, a KCVA-based contributions is proposed using the state subspace and the residual subspace which can isolate the faulty variables effectively. Simulations are conducted on the Tennessee Eastman process to verify the performance of the proposed method.
This work focuses on a class of general decentralized constraint-coupled optimization problems. We propose a novel nested primal-dual gradient algorithm (NPGA), which can achieve linear convergence under the weakest k...
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Recently, Transformer-based methods for single image super-resolution (SISR) have achieved better performance advantages than the methods based on convolutional neural network (CNN). Exploiting self-attention mechanis...
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Emotion Recognition in Conversation (ERC) plays a significant part in Human-Computer Interaction (HCI) systems since it can provide empathetic services. Multimodal ERC can mitigate the drawbacks of uni-modal approache...
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A class of distributed optimization problem with a globally coupled equality constraint and local constrained sets is studied in this paper. For its special case where local constrained sets are absent, an augmented p...
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An extensive amount of research applications on traffic flow prediction models taking into account spatio-temporal modeling have been undertaken in recent years. Relative to traditional spatio-temporal modeling approa...
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For battery management systems, it is significant to reliably estimate state-of-charge (SOC) from limited measurements in real time. Based on a nonlinear SOC-dependent equivalent circuit model, we propose a real-time ...
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Multimodal sentiment analysis (MSA) is a fundamental complex research problem due to the heterogeneity gap between different modalities and the ambiguity of human emotional expression. Although there have been many su...
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An improved adaptive variational Bayesian (VB) nonlinear filter is proposed. Through Cubature sampling, inverse Wishart distribution is introduced to jointly estimate system states and inaccurate measurement noise for...
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