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20192023
most citedRethinking the Item Order in Session-based Recommendation with Graph Neural Networks

339 citations · 849 across the 27 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

stat.ML2021

Spectrum Gaussian Processes Based On Tunable Basis Functions

Wenqi Fang, Guanlin Wu, Jingjing Li +3

Spectral approximation and variational inducing learning for the Gaussian process are two popular methods to reduce computational complexity. However, in previous research, those m…

cs.IR2021★ 147 cited

Exploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks

Ruihong Qiu, Zi Huang, Jingjing Li +1

Different from the traditional recommender system, the session-based recommender system introduces the concept of the session, i.e., a sequence of interactions between a user and m…

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.CV2021★ 8 cited

Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation

Zhekai Du, Jingjing Li, Hongzu Su +2

Unsupervised Domain Adaptation (UDA) aims to generalize the knowledge learned from a well-labeled source domain to an unlabeled target domain. Recently, adversarial domain adaptati…

cs.CV2021★ 2 cited

Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning

Zhi Chen, Zi Huang, Jingjing Li +1

Compared to conventional zero-shot learning (ZSL) where recognising unseen classes is the primary or only aim, the goal of generalized zero-shot learning (GZSL) is to recognise bot…