2020
Transfer Learning via $\ell_1$ Regularization
NeurIPS 2020poster
Machine learning algorithms typically require abundant data under a stationary environment. However, environments are nonstationary in many real-world applications. Critical issues lie in how to effectively adapt models under an ever-changing environment. We propose a method for transferring knowled…