Wenliang Zhong

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 34

Top Topics

Multiple Instance

Graph Representation

Top Venues

Publications

Chunjing Gan, Binbin Hu, Bo Huang, Ziqi Liu, Jian Ma, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou
Your decision path does matter in pre-training industrial recommenders with multi-source behaviors. CoRR (2024)
Wenliang Zhong, Wenyi Wu, Qi Li, Robert A. Barton, Boxin Du, Shioulin Sam, Karim Bouyarmane, Ismail B. Tutar, Junzhou Huang
Enhancing Multimodal Large Language Models with Multi-instance Visual Prompt Generator for Visual Representation Enrichment. CoRR (2024)
Wenyi Wu, Qi Li, Wenliang Zhong, Junzhou Huang
MIVC: Multiple Instance Visual Component for Visual-Language Models. WACV (2024)
Sicong Xie, Qunwei Li, Weidi Xu, Kaiming Shen, Shaohu Chen, Wenliang Zhong
Denoising Time Cycle Modeling for Recommendation. CoRR (2024)
Wenliang Zhong, Haoyu Tang, Qinghai Zheng, Mingzhu Xu, Yupeng Hu, Liqiang Nie
Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory. CoRR (2024)
Feng Jiang, Yuzhi Guo, Hehuan Ma, Saiyang Na, Wenliang Zhong, Yi Han, Tao Wang, Junzhou Huang
GTE: a graph learning framework for prediction of T-cell receptors and epitopes binding specificity. Briefings Bioinform. 25 (4) (2024)
Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. WSDM (2024)
Qifeng Zhou, Wenliang Zhong, Yuzhi Guo, Michael Xiao, Hehuan Ma, Junzhou Huang
PathM3: A Multimodal Multi-Task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning. CoRR (2024)
Yue Liu, Shihao Zhu, Jun Xia, Yingwei Ma, Jian Ma, Wenliang Zhong, Guannan Zhang, Kejun Zhang, Xinwang Liu
End-to-end Learnable Clustering for Intent Learning in Recommendation. CoRR (2024)
Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang, Chenliang Li, Fajie Yuan
Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset. SIGIR (2024)
Wenyi Wu, Qi Li, Wenliang Zhong, Junzhou Huang
MIVC: Multiple Instance Visual Component for Visual-Language Models. CoRR (2023)
Sicong Xie, Binbin Hu, Fengze Li, Ziqi Liu, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou
COUPA: An Industrial Recommender System for Online to Offline Service Platforms. CoRR (2023)
Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. CoRR (2023)
Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu
Edge-cloud Collaborative Learning with Federated and Centralized Features. CoRR (2023)
Xiaoling Zang, Binbin Hu, Jun Chu, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong
Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay. KDD (2023)
Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. CoRR (2023)
Yucheng Shi, Hehuan Ma, Wenliang Zhong, Gengchen Mai, Xiang Li, Tianming Liu, Junzhou Huang
ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs. CoRR (2023)
Yucheng Shi, Hehuan Ma, Wenliang Zhong, Qiaoyu Tan, Gengchen Mai, Xiang Li, Tianming Liu, Junzhou Huang
ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs. ICDM (Workshops) (2023)
Youru Li, Xiaobo Guo, Wenfang Lin, Mingjie Zhong, Qunwei Li, Zhongyi Liu, Wenliang Zhong, Zhenfeng Zhu
Learning Dynamic User Interest Sequence in Knowledge Graphs for Click-Through Rate Prediction. IEEE Trans. Knowl. Data Eng. 35 (1) (2023)
Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. SIGIR (2023)
Sicong Xie, Binbin Hu, Fengze Li, Ziqi Liu, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou
COUPA: An Industrial Recommender System for Online to Offline Service Platforms. SIGIR (2023)
Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu
Edge-cloud Collaborative Learning with Federated and Centralized Features. SIGIR (2023)
Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang
C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction. CoRR (2023)
Sicong Xie, Qunwei Li, Weidi Xu, Kaiming Shen, Shaohu Chen, Wenliang Zhong
Denoising Time Cycle Modeling for Recommendation. SIGIR (2022)
Ningning Li, Qunwei Li, Xichen Ding, Shaohu Chen, Wenliang Zhong
Prototypical Contrastive Learning and Adaptive Interest Selection for Candidate Generation in Recommendations. CIKM (2022)
Yuehua Zhu, Bo Huang, Shaohua Jiang, Muli Yang, Yanhua Yang, Wenliang Zhong
Progressive Self-Attention Network with Unsymmetrical Positional Encoding for Sequential Recommendation. SIGIR (2022)
Shiji Zhou, Wenpeng Zhang, Jiyan Jiang, Wenliang Zhong, Jinjie Gu, Wenwu Zhu
On the Convergence of Stochastic Multi-Objective Gradient Manipulation and Beyond. NeurIPS (2022)
Yu Ma, Zhining Liu, Chenyi Zhuang, Yize Tan, Yi Dong, Wenliang Zhong, Jinjie Gu
Non-stationary Time-aware Kernelized Attention for Temporal Event Prediction. KDD (2022)
Ningning Li, Qunwei Li, Xichen Ding, Shaohu Chen, Wenliang Zhong
Prototypical Contrastive Learning and Adaptive Interest Selection for Candidate Generation in Recommendations. CoRR (2022)
Xingyu Lu, Qintong Wu, Wenliang Zhong
Multi-slots Online Matching with High Entropy. ICML (2022)
Qunwei Li, Shaofeng Zou, Wenliang Zhong
Learning Graph Neural Networks with Approximate Gradient Descent. AAAI (2021)
Qunwei Li, Shaofeng Zou, Wenliang Zhong
Learning Graph Neural Networks with Approximate Gradient Descent. CoRR (2020)
Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi
Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing. CoRR (2020)
Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi
Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing. CIKM (2019)
Quanming Yao, James Tin-Yau Kwok, Wenliang Zhong
Fast Low-Rank Matrix Learning with Nonconvex Regularization. CoRR (2015)
Quanming Yao, James T. Kwok, Wenliang Zhong
Fast Low-Rank Matrix Learning with Nonconvex Regularization. ICDM (2015)
Wenliang Zhong, Rong Jin, Cheng Yang, Xiaowei Yan, Qi Zhang, Qiang Li
Stock Constrained Recommendation in Tmall. KDD (2015)
Wenliang Zhong, James Tin-Yau Kwok
Accelerated Stochastic Gradient Method for Composite Regularization. AISTATS (2014)
Xu Guo, Weisheng Zhang, Wenliang Zhong
Topology optimization based on moving deformable components: A new computational framework. CoRR (2014)
Wenliang Zhong, James Tin-Yau Kwok
Fast Stochastic Alternating Direction Method of Multipliers. ICML (2014)
Wenliang Zhong, James T. Kwok
Gradient Descent with Proximal Average for Nonconvex and Composite Regularization. AAAI (2014)
Wenliang Zhong, James T. Kwok
Accurate Probability Calibration for Multiple Classifiers. IJCAI (2013)
Wenliang Zhong, James Tin-Yau Kwok
Convex Multitask Learning with Flexible Task Clusters. ICML (2012)
Wenliang Zhong, James Tin-Yau Kwok
Convex Multitask Learning with Flexible Task Clusters CoRR (2012)
Wenliang Zhong, James T. Kwok
Efficient Sparse Modeling with Automatic Feature Grouping. ICML (2011)
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. Tsang
Incorporating the loss function into discriminative clustering of structured outputs. IEEE Trans. Neural Networks 21 (10) (2010)