Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments (Review)

#multitasklearning #biology #neuralnetworks Catastrophic forgetting is a big problem in mutli-task and continual learning. Gradients of different objectives tend to conflict, and new tasks tend to override past knowledge. In biological neural networks, each neuron carries a complex network of dendrites that mitigate such forgetting by recognizing the context of an input signal. This paper introduces Active Dendrites, which carries over the principle of context-sensitive gating by dendrites into the deep learning world. Various experiments show the benefit in combatting catastrophic forgetting, while preserving sparsity and limited parameter counts. OUTLINE: 0:00 - Introduction 1:20 - Paper Overview 3:15 - Catastrophic forgetting in continuous and multi-task learning 9:30 - Dendrites in biological neurons 16:55 - Sparse representations in biology 18:35 - Active dendrites in deep learning 34:15 - Experiments on multi-task learning 39:00 - Experiments in continual learning and adaptive prototyping 49:20 - Anal