167 citations · 526 across the 20 of their papers we have counts for
20 papers
Few-Shot Domain Adaptation for Charge Prediction on Unprofessional Descriptions
Jie Zhao, Ziyu Guan, Wei Zhao +2
Recent works considering professional legal-linguistic style (PLLS) texts have shown promising results on the charge prediction task. However, unprofessional users also show an inc…
Pseudo Contrastive Learning for Graph-based Semi-supervised Learning
Weigang Lu, Ziyu Guan, Wei Zhao +5
Pseudo Labeling is a technique used to improve the performance of semi-supervised Graph Neural Networks (GNNs) by generating additional pseudo-labels based on confident predictions…
Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering
Yaming Yang, Ziyu Guan, Zhe Wang +4
Recent self-supervised pre-training methods on Heterogeneous Information Networks (HINs) have shown promising competitiveness over traditional semi-supervised Heterogeneous Graph N…
Entropy Induced Pruning Framework for Convolutional Neural Networks
Yiheng Lu, Ziyu Guan, Yaming Yang +3
Structured pruning techniques have achieved great compression performance on convolutional neural networks for image classification task. However, the majority of existing methods…
Reliable Community Search in Dynamic Networks
Yifu Tang, Jianxin Li, Nur Al Hasan Haldar +3
Searching for local communities is an important research problem that supports advanced data analysis in various complex networks, such as social networks, collaboration networks,…
SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks
Weigang Lu, Yibing Zhan, Binbin Lin +6
Graph Convolutional Networks (GCNs) suffer from performance degradation when models go deeper. However, earlier works only attributed the performance degeneration to over-smoothing…
AP-10K: A Benchmark for Animal Pose Estimation in the Wild
Hang Yu, Yufei Xu, Jing Zhang +3
Accurate animal pose estimation is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife conservation.…
Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
Ziyu Guan, Hongchang Wu, Qingyu Cao +7
Bid optimization for online advertising from single advertiser's perspective has been thoroughly investigated in both academic research and industrial practice. However, existing w…
Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction
Ruijing Yang, Ziyu Guan, Zitong Yu +3
Automatic pain recognition is paramount for medical diagnosis and treatment. The existing works fall into three categories: assessing facial appearance changes, exploiting physiolo…
Interpretable and Efficient Heterogeneous Graph Convolutional Network
Yaming Yang, Ziyu Guan, Jianxin Li +3
Graph Convolutional Network (GCN) has achieved extraordinary success in learning effective task-specific representations of nodes in graphs. However, regarding Heterogeneous Inform…
Convolutional Hierarchical Attention Network for Query-Focused Video Summarization
Shuwen Xiao, Zhou Zhao, Zijian Zhang +2
Previous approaches for video summarization mainly concentrate on finding the most diverse and representative visual contents as video summary without considering the user's prefer…
IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation
Jun Zhao, Zhou Zhou, Ziyu Guan +4
The remarkable progress of network embedding has led to state-of-the-art algorithms in recommendation. However, the sparsity of user-item interactions (i.e., explicit preferences)…
Personalized Attraction Enhanced Sponsored Search with Multi-task Learning
Wei Zhao, Boxuan Zhang, Beidou Wang +6
We study a novel problem of sponsored search (SS) for E-Commerce platforms: how we can attract query users to click product advertisements (ads) by presenting them features of prod…
Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU
Yu Zhu, Yu Gong, Qingwen Liu +6
Recently, interactive recommender systems are becoming increasingly popular. The insight is that, with the interaction between users and the system, (1) users can actively interven…
Exact-K Recommendation via Maximal Clique Optimization
Yu Gong, Yu Zhu, Lu Duan +5
This paper targets to a novel but practical recommendation problem named exact-K recommendation. It is different from traditional top-K recommendation, as it focuses more on (const…
Addressing the Item Cold-start Problem by Attribute-driven Active Learning
Yu Zhu, Jinhao Lin, Shibi He +4
In recommender systems, cold-start issues are situations where no previous events, e.g. ratings, are known for certain users or items. In this paper, we focus on the item cold-star…
A Brand-level Ranking System with the Customized Attention-GRU Model
Yu Zhu, Junxiong Zhu, Jie Hou +4
In e-commerce websites like Taobao, brand is playing a more important role in influencing users' decision of click/purchase, partly because users are now attaching more importance…
Deep Reinforcement Learning for Sponsored Search Real-time Bidding
Jun Zhao, Guang Qiu, Ziyu Guan +2
Bidding optimization is one of the most critical problems in online advertising. Sponsored search (SS) auction, due to the randomness of user query behavior and platform nature, us…
Efficient Destination Prediction Based on Route Choices with Transition Matrix Optimization
Zhou Yang, Heli Sun, Jianbin Huang +3
Destination prediction is an essential task in a variety of mobile applications. In this paper, we optimize the matrix operation and adapt a semi-lazy framework to improve the pred…
Measuring Two-Event Structural Correlations on Graphs
Ziyu Guan, Xifeng Yan, Lance M. Kaplan
Real-life graphs usually have various kinds of events happening on them, e.g., product purchases in online social networks and intrusion alerts in computer networks. The occurrence…