Z
Zeyu Li
Researcher at University of California, Los Angeles
Publications - 32
Citations - 636
Zeyu Li is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 5, co-authored 12 publications receiving 383 citations. Previous affiliations of Zeyu Li include Harbin Institute of Technology.
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Proceedings ArticleDOI
Learning Gender-Neutral Word Embeddings
TL;DR: This article proposed a novel training procedure for learning gender-neutral word embeddings, which aims to preserve gender information in certain dimensions of word vectors while compelling other dimensions to be free of gender influence.
Posted Content
Learning Gender-Neutral Word Embeddings
TL;DR: A novel training procedure for learning gender-neutral word embeddings that preserves gender information in certain dimensions of word vectors while compelling other dimensions to be free of gender influence is proposed.
Proceedings ArticleDOI
Interpretable Click-Through Rate Prediction through Hierarchical Attention
TL;DR: InterHAt is proposed that employs a Transformer with multi-head self-attention for feature learning that captures high-order feature interactions by an efficient attentional aggregation strategy with low computational complexity.
Journal ArticleDOI
Personalized Question Routing via Heterogeneous Network Embedding
TL;DR: Experimental results show that NeRank significantly outperforms competitive baseline question routing models that ignore the raiser information in three ranking metrics, and is convergeable in several thousand iterations and insensitive to parameter changes, which prove its effectiveness, scalability, and robustness.
Proceedings ArticleDOI
You Are What and Where You Are: Graph Enhanced Attention Network for Explainable POI Recommendation
TL;DR: Zhang et al. as discussed by the authors proposed GEAPR, a POI recommender that is able to interpret the POI prediction in an end-to-end fashion by aggregating different factors, such as structural context, neighbor impact, user attributes, and geolocation influence.