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Interactive Personalization of Classifiers for Explainability using Multi-Objective Bayesian Optimization

Explainability is a crucial aspect of models which ensures their reliable use by both engineers and end-users. However, explainability depends on the user and the model’s usage context, making it an important dimension for user personalization. In …

DSDCS: Detection of Safe Driving via Crowd Sensing

Traffic safety plays an important role in smart transportation, and it has become a social issue worthy of attention. For detection of safe driving, we focus on the collection, processing, distribution, exchange, analysis and utilization of …