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MSQPSO-Optimized MSCC-CAE for Sensor Fault Detection and Localization in Small Modular Reactors. [PDF]
Sensors (Basel)Zhang W, Wan X, Li X, He Z, Luo M.
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Binary classification of signal and background triggers of a transition edge sensor using convolutional neural networks. [PDF]
Sci RepRivasto E +7 more
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A Hybrid CNN-GRU-SE Forecasting Method for Short-Term Photovoltaic Power Considers AFD and Data Aggregation. [PDF]
Entropy (Basel)Liu K +5 more
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Reproducible Hyperparameter Optimization
Journal of Computational and Graphical Statistics, 2021A key issue in machine learning research is the lack of reproducibility. We illustrate what role hyperparameter search plays in this problem and how regular hyperparameter search methods can lead t...
Lars Hertel +2 more
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Hyperparameter Optimization Machines
2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2016Algorithm selection and hyperparameter tuning are omnipresent problems for researchers and practitioners. Hence, it is not surprising that the efforts in automatizing this process using various meta-learning approaches have been increased. Sequential model-based optimization (SMBO) is ne of the most popular frameworks for finding optimal hyperparameter
Martin Wistuba +2 more
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Gradient-Based Optimization of Hyperparameters
Neural Computation, 2000Many machine learning algorithms can be formulated as the minimization of a training criterion that involves a hyperparameter. This hyperparameter is usually chosen by trial and error with a model selection criterion. In this article we present a methodology to optimize several hyper-parameters, based on the computation of the gradient of a model ...
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