Teleoscope enables thematic curation of large Reddit corpora via interactive refinement, with three deployments indicating benefits in serendipitous keyword discovery, search saturation confidence, and collaborative curation discussions.
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Introduces a parallel joint symbolic approximation technique for large-scale time series via local-global decoupling that maintains reconstruction quality with reduced runtime.
A CBR system based on similarity of local explanations provides visualizations that fraud analysts at a Dutch bank found useful and easy to use for processing ML-generated fraud alerts.
Human-grounded evaluation finds no significant performance improvement from adding SHAP explanations to model confidence scores in alert processing.
A seq2seq model is proposed to learn universal embeddings from wearable and ambient sensor data for ADL recognition and semi-supervised learning.
A methodology is proposed to detect class-based concept drift by self-evaluating predictive model degradation, with experiments on synthetic and real-world datasets showing effectiveness.