154 citations · 161 across the 5 of their papers we have counts for
5 papers
SUM: Suboptimal Unitary Multi-task Learning Framework for Spatiotemporal Data Prediction
Qichen Li, Jiaxin Pei, Jianding Zhang +1
The typical multi-task learning methods for spatio-temporal data prediction involve low-rank tensor computation. However, such a method have relatively weak performance when the ta…
Revisiting Sample Selection Approach to Positive-Unlabeled Learning: Turning Unlabeled Data into Positive rather than Negative
Miao Xu, Bingcong Li, Gang Niu +2
In the early history of positive-unlabeled (PU) learning, the sample selection approach, which heuristically selects negative (N) data from U data, was explored extensively. Howeve…
How does Disagreement Help Generalization against Label Corruption?
Xingrui Yu, Bo Han, Jiangchao Yao +3
Learning with noisy labels is one of the hottest problems in weakly-supervised learning. Based on memorization effects of deep neural networks, training on small-loss instances bec…
DATELINE: Deep Plackett-Luce Model with Uncertainty Measurements
Bo Han
The aggregation of k-ary preferences is a historical and important problem, since it has many real-world applications, such as peer grading, presidential elections and restaurant r…
RMSE-ELM: Recursive Model based Selective Ensemble of Extreme Learning Machines for Robustness Improvement
Bo Han, Bo He, Mengmeng Ma +3
Extreme learning machine (ELM) as an emerging branch of shallow networks has shown its excellent generalization and fast learning speed. However, for blended data, the robustness o…