activity
20192023
most citedExploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks

147 citations · 440 across the 18 of their papers we have counts for

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Showing 2019Show all

12 papers · 1 filter

cs.IR2019

Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks

Ruihong Qiu, Jingjing Li, Zi Huang +1

Predicting a user's preference in a short anonymous interaction session instead of long-term history is a challenging problem in the real-life session-based recommendation, e.g., e…

cs.CV2019

CANZSL: Cycle-Consistent Adversarial Networks for Zero-Shot Learning from Natural Language

Zhi Chen, Jingjing Li, Yadan Luo +2

Existing methods using generative adversarial approaches for Zero-Shot Learning (ZSL) aim to generate realistic visual features from class semantics by a single generative network,…

cs.CV2019

Cycle-consistent Conditional Adversarial Transfer Networks

Jingjing Li, Erpeng Chen, Zhengming Ding +3

Domain adaptation investigates the problem of cross-domain knowledge transfer where the labeled source domain and unlabeled target domain have distinctive data distributions. Recen…

cs.CV2019

Alleviating Feature Confusion for Generative Zero-shot Learning

Jingjing Li, Mengmeng Jing, Ke Lu +3

Lately, generative adversarial networks (GANs) have been successfully applied to zero-shot learning (ZSL) and achieved state-of-the-art performance. By synthesizing virtual unseen…

cs.CV2019

Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation

Yadan Luo, Zi Huang, Zheng Zhang +3

Visual paragraph generation aims to automatically describe a given image from different perspectives and organize sentences in a coherent way. In this paper, we address three criti…

cs.CV2019

Agile Domain Adaptation

Jingjing Li, Mengmeng Jing, Yue Xie +2

Domain adaptation investigates the problem of leveraging knowledge from a well-labeled source domain to an unlabeled target domain, where the two domains are drawn from different d…