Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习 ...

To address this problem, we present a new approach to active domain adaptation called Local Uncertainty Energy Transfer (LUET), which integrates active learning of local uncertainty confusion and ...

Transfer Learning for Reinforcement Learning Domains: A Survey. Matthew E. Taylor and Peter Stone. Journal of Machine Learning Research, 10(1):1633–1685, 2009.

Conditional Distribution,Convolutional Neural Network,Deep Convolutional Neural Network,Deep Learning,Deep Network,Deep Neural Network,Deep Transfer Learning,Domain Adaptation,Domain ...

Learn how to handle heterogeneity in deep learning models using data preprocessing, feature engineering, model architecture, and loss function design.

Techniques such as transfer learning, domain adaptation, meta-learning, few-shot learning, active learning, etc. These techniques are critical to the deployment of AI models for real-world ophthalmic ...