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Measuring Affective and Motivational States as Conditions for Cognitive and Metacognitive Processing in Self-Regulated Learning.

, , , , , , , , , , , and . LAK, page 701-712. ACM, (2024)

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Emergent and Unspecified Behaviors in Streaming Decision Trees., , , and . CoRR, (2020)Proximity Forest 2.0: A new effective and scalable similarity-based classifier for time series., , , and . CoRR, (2023)Improving Position Encoding of Transformers for Multivariate Time Series Classification., , , and . CoRR, (2023)ENDASh: Embedding Neighbourhood Dissimilarity with Attribute Shuffling for Graph Anomaly Detection., , , , and . PAKDD (2), volume 13281 of Lecture Notes in Computer Science, page 17-29. Springer, (2022)Robust Demand Response for Device Scheduling under False Data Injection Attacks in Smart Grids., , , and . ISGT-Europe, page 294-298. IEEE, (2020)High Impact False Data Injection Attack against Real-time Pricing in Smart Grids., , , , and . ISGT Europe, page 1-5. IEEE, (2019)Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignment., , , , and . CoRR, (2022)An Eager Splitting Strategy for Online Decision Trees., , , , and . CoRR, (2020)Improving position encoding of transformers for multivariate time series classification., , , and . Data Min. Knowl. Discov., 38 (1): 22-48 (January 2024)Deep Learning for Time Series Anomaly Detection: A Survey., , , , and . CoRR, (2022)