23 citations · 72 across the 11 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 4 cited
MetaInfoNet: Learning Task-Guided Information for Sample Reweighting
Hongxin Wei, Lei Feng, Rundong Wang +1
Deep neural networks have been shown to easily overfit to biased training data with label noise or class imbalance. Meta-learning algorithms are commonly designed to alleviate this…
cs.LG2020★ 10 cited
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning
Zhuowei Wang, Jing Jiang, Bo Han +4
Deep learning with noisy labels is a challenging task. Recent prominent methods that build on a specific sample selection (SS) strategy and a specific semi-supervised learning (SSL…
cs.IR2020★ 3 cited
GLIMG: Global and Local Item Graphs for Top-N Recommender Systems
Zhuoyi Lin, Lei Feng, Rui Yin +2
Graph-based recommendation models work well for top-N recommender systems due to their capability to capture the potential relationships between entities. However, most of the exis…