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Semantic Properties of Cosine Based Bias Scores for Word Embeddings.

, , , and . ICPRAM, page 160-168. SCITEPRESS, (2024)

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Investigating the Suitability of Concept Drift Detection for Detecting Leakages in Water Distribution Networks., , and . ICPRAM, page 296-303. SCITEPRESS, (2024)The SAME score: Improved cosine based bias score for word embeddings., , , , , and . CoRR, (2022)Localization of Concept Drift: Identifying the Drifting Datapoints., , , , and . IJCNN, page 1-9. IEEE, (2022)DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction., , and . IJCAI, page 2305-2311. ijcai.org, (2020)Scheduled for July 2020, Yokohama, Japan, postponed due to the Corona pandemic..Federated learning vector quantization for dealing with drift between nodes., , , , , and . ESANN, (2022)Evaluating Metrics for Bias in Word Embeddings., , , , , and . CoRR, (2021)Precise Change Point Detection using Spectral Drift Detection., , , and . CoRR, (2022)Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information., , , , , and . CoRR, (2019)Semantic Properties of Cosine Based Bias Scores for Word Embeddings., , , and . ICPRAM, page 160-168. SCITEPRESS, (2024)DeepView: Visualizing the behavior of deep neural networks in a part of the data space., , and . CoRR, (2019)