Machine Learning and Knowledge Discovery in Databases. Research Track

The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions.
The volumes are organized in topical sections as follows:
Research Track:
Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications.
Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety.
Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics.
Applied Data Science Track:
Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation.
Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.
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