93 citations · 98 across the 5 of their papers we have counts for
3 papers
cs.CV2021★ 1 cited
Long-tail Recognition via Compositional Knowledge Transfer
Sarah Parisot, Pedro M. Esperanca, Steven McDonagh +3
In this work, we introduce a novel strategy for long-tail recognition that addresses the tail classes' few-shot problem via training-free knowledge transfer. Our objective is to tr…
cs.LG2016
Unifying Multi-Domain Multi-Task Learning: Tensor and Neural Network Perspectives
Yongxin Yang, Timothy M. Hospedales
Multi-domain learning aims to benefit from simultaneously learning across several different but related domains. In this chapter, we propose a single framework that unifies multi-d…
stat.ML2014★ 93 cited
A Unified Perspective on Multi-Domain and Multi-Task Learning
Yongxin Yang, Timothy M. Hospedales
In this paper, we provide a new neural-network based perspective on multi-task learning (MTL) and multi-domain learning (MDL). By introducing the concept of a semantic descriptor,…