Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

"Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time-Series Forecas… https://t.co/E1KqyXuAxN

Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time-Series Forecast. Jens Schreiber, Stephan Vogt, and Bernhard Sick https://t.co/6BVv3Rw6Sa

Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time-Series Forecast. (arXiv:2204.13908v1 [cs.LG]) https://t.co/6DlKL42SHQ

📜L. Zigrand, PhD Student @LipnLab, and his coauthors had a paper accepted to @ECMLPKDD. They propose to optimize Demand-Responsive Transport services using Simulations, Machine Learning & Combinatorial Optimization to exploit their historical data. 🔗