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BibTeX (Download)
@{,
keywords = {anomaly detection, averaging, batch normalization, biology, black-box, black-box, black-box parallelization, black-box parallelization, black-box parallelization, causal discovery, causal discovery, causality, causality, chemistry, co-regularization, communication-efficient, communication-efficient, complexity, convex optimization, corresponding projections, corresponding projections, cybersecurity, daisy, daisy-chaining, decentralized, decentralized, deep learning, deep learning, deep learning, deep learning, deep learning, deep learning, deep learning, deep learning, DiSIEM, DiSIEM, distributed, distributed, distributed, distributed learning, dynamic averaging, dynamic averaging, edge computing, embedded, explainability, explainable, exponential family, FedDC, federated, federated, federated, federated causal discovery, federated causal discovery, federated learning, federated learning, federated learning, federated learning, federated learning, federated learning, federated learning, federated learning, flatness, flatness, flatness, flatness, FPGA, generalization, generalization, generalization, generalization, Hessian, industry 4.0, interpretability, interpretable, interpretable, interpretable, intervention, kernel methods, layer-wise, learning theory, learning theory, learning theory, learning theory, linear mode connectivity, loss surface, loss surface, machine learning, machine learning, machine learning, machine learning, machine learning, machine learning, neural networks, neural networks, parallelization, parallelization, parallelization, privacy, radon, radon machine, relative flatness, relative flatness, resource-efficient, robustness, robustness, rule ensemble, rule learning, rule mining, security, semi-supervised, SIEM, small, small datasets, smart production, theory of deep learning, theory of deep learning, transfer learning, transfer learning, uncertainty, uncertainty, unsupervised, unsupervised, user behavior modelling, visual analytics, visualization, visualization, XAI, XAI},
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}