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4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022.

, , , , , , , , , , , , and . KDD, page 4860-4861. ACM, (2022)

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ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids., , , , and . IEEE Access, (2020)CPDGA: Change point driven growing auto-encoder for lifelong anomaly detection., , and . Knowl. Based Syst., (2022)Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification., , , and . IJCNN, page 1-7. IEEE, (2021)LIFEWATCH: Lifelong Wasserstein Change Point Detection., , , , and . IJCNN, page 1-8. IEEE, (2022)The class imbalance problem in deep learning., , , , , and . Mach. Learn., 113 (7): 4845-4901 (July 2024)Towards Efficient Deep Autoencoders for Multivariate Time Series Anomaly Detection., , , and . ICCS (3), volume 14834 of Lecture Notes in Computer Science, page 461-469. Springer, (2024)Distributed Continual Intrusion Detection: A Collaborative Replay Framework., , and . IEEE Big Data, page 3255-3263. IEEE, (2023)AD-NEv++ - The multi-architecture neuroevolution-based multivariate anomaly detection framework., , , , and . GECCO Companion, page 607-610. ACM, (2024)Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification., , , , , and . Sensors, 20 (14): 3906 (2020)Spatial autocorrelation and entropy for renewable energy forecasting, , , and . Data Mining and Knowledge Discovery, 33 (3): 698--729 (2019)