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Continuous diagnosis and prognosis by controlling the update process of deep neural networks.

, , , , , and . Patterns, 4 (2): 100687 (February 2023)

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Dlsa: Semi-supervised partial label learning via dependence-maximized label set assignment., , , , and . Inf. Sci., (2022)GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization., , , , , and . SDM, page 451-458. SIAM, (2022)TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data., , , , , , and . IJCAI, page 3010-3016. ijcai.org, (2021)Time pattern reconstruction for classification of irregularly sampled time series., , , , , and . Pattern Recognit., (March 2024)Continuous diagnosis and prognosis by controlling the update process of deep neural networks., , , , , and . Patterns, 4 (2): 100687 (February 2023)TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data., , , , , , and . CoRR, (2021)GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization., , , , , and . CoRR, (2021)Curricular and Cyclical Loss for Time Series Learning Strategy., , , , and . CoRR, (2023)Deep Ordinal Neural Network for Length of Stay Estimation in the Intensive Care Units., , , , , and . CIKM, page 3843-3847. ACM, (2022)Confidence-Guided Learning Process for Continuous Classification of Time Series., , , , , and . CIKM, page 4525-4529. ACM, (2022)