Lifelong Learning with Dynamically Expandable Networks

ICLR 2018

Lifelong Learning with Dynamically Expandable Networks

Jaehong Yoon, Eunho Yang, Jeongtae Lee, Sungju Hwang

We propose a novel deep network architecture for lifelong learning which we refer to as Dynamically Expandable Network (DEN), that can dynamically decide its network capacity as it trains on a sequence of tasks, to learn a compact overlapping knowledge sharing structure among tasks.

Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding

MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning

PUBLICATIONS

Lifelong Learning with Dynamically Expandable Networks