2 papers
cs.CV2022
Compare learning: bi-attention network for few-shot learning
Li Ke, Meng Pan, Weigao Wen +1
Learning with few labeled data is a key challenge for visual recognition, as deep neural networks tend to overfit using a few samples only. One of the Few-shot learning methods cal…
cs.CL2021
InfoBehavior: Self-supervised Representation Learning for Ultra-long Behavior Sequence via Hierarchical Grouping
Runshi Liu, Pengda Qin, Yuhong Li +4
E-commerce companies have to face abnormal sellers who sell potentially-risky products. Typically, the risk can be identified by jointly considering product content (e.g., title an…