Darshan Patil

Loss Smoothing for Stable Adaptation Under Distribution Shift

Darshan Patil, Ekaterina Lobacheva, Razvan Pascanu, Sarath Chandar

In settings such as fine-tuning and reinforcement learning, neural networks are often adapted under distribution shift. Standard adaptation methods typically optimize the target objective directly, inducing an abrupt change from the source training objective. This abrupt transiti…Read more