Machine Learning and Knowledge Discovery in Databases
Description
The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track.
The contributions were organized in topical sections named as follows:
Part I: pattern mining; clustering, anomaly and outlier detection, and autoencoders; dimensionality reduction and feature selection; social networks and graphs; decision trees, interpretability, and causality; strings and streams; privacy and security; optimization.
Part II: supervised learning; multi-label learning; large-scale learning; deep learning; probabilistic models; natural language processing.
Part III: reinforcement learning and bandits; ranking; applied data science: computer vision and explanation; applied data science: healthcare; applied data science: e-commerce, finance, and advertising; applied data science: rich data; applied data science: applications; demo track.
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Content
Reinforcement Learning and Bandits.- Ranking.- Applied Data Science: Computer Vision and Explanation.- Applied Data Science: Healthcare.- Applied Data Science: E-commerce, Finance, and Advertising.- Applied Data Science: Rich Data.- Applied Data Science: Applications.- Demo Track.
