Search Results for author: Yinliang Yue

Found 5 papers, 2 papers with code

Learning Explicit User Interest Boundary for Recommendation

1 code implementation22 Nov 2021 Jianhuan Zhuo, Qiannan Zhu, Yinliang Yue, Yuhong Zhao

The core objective of modelling recommender systems from implicit feedback is to maximize the positive sample score $s_p$ and minimize the negative sample score $s_n$, which can usually be summarized into two paradigms: the pointwise and the pairwise.

Recommendation Systems

Learning Better Representation for Tables by Self-Supervised Tasks

no code implementations15 Oct 2020 Liang Li, Can Ma, Yinliang Yue, Linjun Shou, Dayong Hu

Secondly, the target texts in training dataset may contain redundant information or facts do not exist in the input tables.

Table-to-Text Generation

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