765 citations · 1.6k across the 39 of their papers we have counts for
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cs.LG2023★ 7 cited
Core-Periphery Principle Guided Redesign of Self-Attention in Transformers
Xiaowei Yu, Lu Zhang, Haixing Dai +6
Designing more efficient, reliable, and explainable neural network architectures is critical to studies that are based on artificial intelligence (AI) techniques. Previous studies,…
cs.LG2022★ 17 cited
Disentangled Representation Learning
Xin Wang, Hong Chen, Si'ao Tang +2
Disentangled Representation Learning (DRL) aims to learn a model capable of identifying and disentangling the underlying factors hidden in the observable data in representation for…
cs.LG2022
Is Multi-Task Learning an Upper Bound for Continual Learning?
Zihao Wu, Huy Tran, Hamed Pirsiavash +1
Continual and multi-task learning are common machine learning approaches to learning from multiple tasks. The existing works in the literature often assume multi-task learning as a…