Titlebook: Discovery Science; 25th International C Poncelet Pascal,Dino Ienco Conference proceedings 2022 The Editor(s) (if applicable) and The Author

mutineer

Hyperparameter Importance of Quantum Neural Networks Across Small Datasets this to 7 open-source datasets from the OpenML-CC18 classification benchmark whose number of features is small enough to fit on quantum hardware with less than 20 qubits. Three main levels of importance were detected from the ranking of hyperparameters obtained with functional ANOVA. Our experiment

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gain631

Adaptive Neural Networks for Online Domain Incremental Continual Learning(TP) is trained to select the most suitable NN from the frozen pool for prediction. We compare ODIN against popular regularization and replay methods. It outperforms regularization methods and achieves comparable predictive performance to replay methods.

CROW

invert

Leveraging Spatio-Temporal Autocorrelation to Improve the Forecasting of the Energy Consumption in S temporal information related to historical measurements using multiple strategies, as well as that of simultaneously predicting multiple future consumption measurements in a multi-step predictive setting. Finally, we investigate the effectiveness of injecting descriptive features to make the learni

tic-douloureux

Elastic Product Quantization for Time Seriesments, which we address with a pre-alignment step using the maximal overlap discrete wavelet transform (MODWT). To demonstrate the efficiency and accuracy of our method, we perform an extensive experimental evaluation on benchmark datasets in nearest neighbors classification and clustering applicati

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UTTER

Data-Driven Prediction of Athletes’ Performance Based on Their Social Media Presence