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20202023
most citedCausalRec: Causal Inference for Visual Debiasing in Visually-Aware Recommendation

35 citations · 93 across the 13 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.IR2021★ 35 cited

CausalRec: Causal Inference for Visual Debiasing in Visually-Aware Recommendation

Ruihong Qiu, Sen Wang, Zhi Chen +2

Visually-aware recommendation on E-commerce platforms aims to leverage visual information of items to predict a user's preference. It is commonly observed that user's attention to…

cs.CV2021

Mitigating Generation Shifts for Generalized Zero-Shot Learning

Zhi Chen, Yadan Luo, Sen Wang +3

Generalized Zero-Shot Learning (GZSL) is the task of leveraging semantic information (e.g., attributes) to recognize the seen and unseen samples, where unseen classes are not obser…

cs.LG2021

How Sensitive are Meta-Learners to Dataset Imbalance?

Mateusz Ochal, Massimiliano Patacchiola, Amos Storkey +2

Meta-Learning (ML) has proven to be a useful tool for training Few-Shot Learning (FSL) algorithms by exposure to batches of tasks sampled from a meta-dataset. However, the standard…

cs.CV2021★ 10 cited

Semantics Disentangling for Generalized Zero-Shot Learning

Zhi Chen, Yadan Luo, Ruihong Qiu +4

Generalized zero-shot learning (GZSL) aims to classify samples under the assumption that some classes are not observable during training. To bridge the gap between the seen and uns…

cs.LG2021★ 4 cited

Few-Shot Learning with Class Imbalance

Mateusz Ochal, Massimiliano Patacchiola, Amos Storkey +2

Few-Shot Learning (FSL) algorithms are commonly trained through Meta-Learning (ML), which exposes models to batches of tasks sampled from a meta-dataset to mimic tasks seen during…