2 papers
cs.IR2024
LiMAML: Personalization of Deep Recommender Models via Meta Learning
Ruofan Wang, Prakruthi Prabhakar, Gaurav Srivastava +10
In the realm of recommender systems, the ubiquitous adoption of deep neural networks has emerged as a dominant paradigm for modeling diverse business objectives. As user bases cont…
cs.LG2024
Towards Continual Learning Desiderata via HSIC-Bottleneck Orthogonalization and Equiangular Embedding
Depeng Li, Tianqi Wang, Junwei Chen +3
Deep neural networks are susceptible to catastrophic forgetting when trained on sequential tasks. Various continual learning (CL) methods often rely on exemplar buffers or/and netw…