Incorporating the loss function into discriminative clustering of structured outputs. - Wenliang Zhong; Weike Pan; James T. Kwok; Ivor W. Tsang (IEEE Trans. Neural Networks, 2010)

Convex Multitask Learning with Flexible Task Clusters. - Wenliang Zhong; James Tin-Yau Kwok (ICML, 2012)

Efficient Sparse Modeling With Automatic Feature Grouping. - Leon Wenliang Zhong; James T. Kwok (IEEE Trans. Neural Networks Learn. Syst., 2012)

Efficient Learning for Models with DAG-Structured Parameter Constraints. - Leon Wenliang Zhong; James T. Kwok (ICDM, 2013)

Accurate Probability Calibration for Multiple Classifiers. - Wenliang Zhong; James T. Kwok (IJCAI, 2013)

Gradient Descent with Proximal Average for Nonconvex and Composite Regularization. - Wenliang Zhong; James T. Kwok (AAAI, 2014)

Accelerated Stochastic Gradient Method for Composite Regularization. - Wenliang Zhong; James Tin-Yau Kwok (AISTATS, 2014)

Fast Stochastic Alternating Direction Method of Multipliers. - Wenliang Zhong; James Tin-Yau Kwok (ICML, 2014)

Topology optimization based on moving deformable components: A new computational framework. - Xu Guo; Weisheng Zhang; Wenliang Zhong (CoRR, 2014)

Fast Low-Rank Matrix Learning with Nonconvex Regularization. - Quanming Yao; James T. Kwok; Wenliang Zhong (ICDM, 2015)

Stock Constrained Recommendation in Tmall. - Wenliang Zhong; Rong Jin 001; Cheng Yang; Xiaowei Yan; Qi Zhang; Qiang Li (KDD, 2015)

Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing. - Ziqi Liu; Dong Wang 062; Qianyu Yu 001; Zhiqiang Zhang 012; Yue Shen; Jian Ma; Wenliang Zhong; Jinjie Gu; Jun Zhou 011; Shuang Yang; Yuan Qi 001 (CIKM, 2019)

Learning Graph Neural Networks with Approximate Gradient Descent. - Qunwei Li; Shaofeng Zou; Wenliang Zhong (AAAI, 2021)

Prototypical Contrastive Learning and Adaptive Interest Selection for Candidate Generation in Recommendations. - Ningning Li; Qunwei Li; Xichen Ding; Shaohu Chen; Wenliang Zhong (CIKM, 2022)

Multi-slots Online Matching with High Entropy. - Xingyu Lu; Qintong Wu; Wenliang Zhong (ICML, 2022)

Non-stationary Time-aware Kernelized Attention for Temporal Event Prediction. - Yu Ma; Zhining Liu 001; Chenyi Zhuang; Yize Tan; Yi Dong; Wenliang Zhong; Jinjie Gu (KDD, 2022)

On the Convergence of Stochastic Multi-Objective Gradient Manipulation and Beyond. - Shiji Zhou; Wenpeng Zhang 003; Jiyan Jiang; Wenliang Zhong; Jinjie Gu; Wenwu Zhu 001 (NeurIPS, 2022)

Denoising Time Cycle Modeling for Recommendation. - Sicong Xie; Qunwei Li; Weidi Xu; Kaiming Shen; Shaohu Chen; Wenliang Zhong (SIGIR, 2022)

Progressive Self-Attention Network with Unsymmetrical Positional Encoding for Sequential Recommendation. - Yuehua Zhu; Bo Huang; Shaohua Jiang; Muli Yang; Yanhua Yang; Wenliang Zhong (SIGIR, 2022)

ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs. - Yucheng Shi; Hehuan Ma; Wenliang Zhong; Qiaoyu Tan; Gengchen Mai; Xiang Li 001; Tianming Liu 001; Junzhou Huang (ICDM (Workshops), 2023)

Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay. - Xiaoling Zang; Binbin Hu; Jun Chu; Zhiqiang Zhang 012; Guannan Zhang; Jun Zhou 011; Wenliang Zhong (KDD, 2023)

Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. - Chunjing Gan; Binbin Hu; Bo Huang; Tianyu Zhao; Yingru Lin; Wenliang Zhong; Zhiqiang Zhang 012; Jun Zhou 011; Chuan Shi 001 (SIGIR, 2023)

Edge-cloud Collaborative Learning with Federated and Centralized Features. - Zexi Li 001; Qunwei Li; Yi Zhou; Wenliang Zhong; Guannan Zhang; Chao Wu 001 (SIGIR, 2023)

COUPA: An Industrial Recommender System for Online to Offline Service Platforms. - Sicong Xie; Binbin Hu; Fengze Li; Ziqi Liu; Zhiqiang Zhang 012; Wenliang Zhong; Jun Zhou 011 (SIGIR, 2023)

ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs. - Yucheng Shi; Hehuan Ma; Wenliang Zhong; Gengchen Mai; Xiang Li 001; Tianming Liu 001; Junzhou Huang (CoRR, 2023)

AntM2C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction. - Zhaoxin Huan; Ke Ding; Ang Li; Xiaolu Zhang; Xu Min; Yong He 009; Liang Zhang; Jun Zhou 011; Linjian Mo; Jinjie Gu; Zhongyi Liu; Wenliang Zhong; et al. (CoRR, 2023)

PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. - Chunjing Gan; Bo Huang; Binbin Hu; Jian Ma; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011; Guannan Zhang; Wenliang Zhong (CoRR, 2023)

Learning Dynamic User Interest Sequence in Knowledge Graphs for Click-Through Rate Prediction. - Youru Li; Xiaobo Guo; Wenfang Lin; Mingjie Zhong; Qunwei Li; Zhongyi Liu; Wenliang Zhong; Zhenfeng Zhu (IEEE Trans. Knowl. Data Eng., 2023)

Towards Efficient Replay in Federated Incremental Learning. - Yichen Li 006; Qunwei Li; Haozhao Wang; Ruixuan Li 001; Wenliang Zhong; Guannan Zhang (CVPR, 2024)

Causal Subgraphs and Information Bottlenecks: Redefining OOD Robustness in Graph Neural Networks. - Weizhi An; Wenliang Zhong; Feng Jiang; Hehuan Ma; Junzhou Huang (ECCV (88), 2024)

RRE: A Relevance Relation Extraction Framework for Cross-domain Recommender System at Alipay. - Jiayang Gu; Xovee Xu; Yulu Tian; Yurun Hu; Jiadong Huang; Wenliang Zhong; Fan Zhou 002; Lianli Gao (ICME, 2024)

PathM3: A Multimodal Multi-task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning. - Qifeng Zhou; Wenliang Zhong; Yuzhi Guo; Michael Xiao; Hehuan Ma; Junzhou Huang (MICCAI (4), 2024)

End-to-end Learnable Clustering for Intent Learning in Recommendation. - Yue Liu; Shihao Zhu; Jun Xia; Yingwei Ma; Jian Ma; Xinwang Liu; Shengju Yu; Kejun Zhang; Wenliang Zhong (NeurIPS, 2024)

Identify Then Recommend: Towards Unsupervised Group Recommendation. - Yue Liu; Shihao Zhu; Tianyuan Yang; Jian Ma; Wenliang Zhong (NeurIPS, 2024)

Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset. - Zhaoxin Huan; Ke Ding; Ang Li; Xiaolu Zhang; Xu Min; Yong He 009; Liang Zhang; Jun Zhou 011; Linjian Mo; Jinjie Gu; Zhongyi Liu; Wenliang Zhong; et al. (SIGIR, 2024)

MIVC: Multiple Instance Visual Component for Visual-Language Models. - Wenyi Wu; Qi Li; Wenliang Zhong; Junzhou Huang (WACV, 2024)

PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. - Chunjing Gan; Bo Huang; Binbin Hu; Jian Ma; Zhiqiang Zhang 012; Jun Zhou 011; Guannan Zhang; Wenliang Zhong (WSDM, 2024)

GTE: a graph learning framework for prediction of T-cell receptors and epitopes binding specificity. - Feng Jiang; Yuzhi Guo; Hehuan Ma; Saiyang Na; Wenliang Zhong; Yi Han; Tao Wang 161; Junzhou Huang (Briefings Bioinform., 2024)

Online Differentiable Clustering for Intent Learning in Recommendation. - Yue Liu; Shihao Zhu; Jun Xia; Yingwei Ma; Jian Ma; Wenliang Zhong; Guannan Zhang; Kejun Zhang; Xinwang Liu (CoRR, 2024)

Your decision path does matter in pre-training industrial recommenders with multi-source behaviors. - Chunjing Gan; Binbin Hu; Bo Huang; Ziqi Liu; Jian Ma; Zhiqiang Zhang 012; Wenliang Zhong; Jun Zhou 011 (CoRR, 2024)

Enhancing Multimodal Large Language Models with Multi-instance Visual Prompt Generator for Visual Representation Enrichment. - Wenliang Zhong; Wenyi Wu; Qi Li; Robert A. Barton; Boxin Du; Shioulin Sam; Karim Bouyarmane; Ismail B. Tutar; Junzhou Huang (CoRR, 2024)

Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory. - Wenliang Zhong; Haoyu Tang; Qinghai Zheng; Mingzhu Xu; Yupeng Hu; Liqiang Nie (CoRR, 2024)

Compositional Image Retrieval via Instruction-Aware Contrastive Learning. - Wenliang Zhong; Weizhi An; Feng Jiang; Hehuan Ma; Yuzhi Guo; Junzhou Huang (CoRR, 2024)

Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory. - Wenliang Zhong; Haoyu Tang; Qinghai Zheng; Mingzhu Xu; Yupeng Hu; Weili Guan (CVPR, 2025)

Contrastive Pretraining for Computational Pathology with Visual-Language Models. - Qifeng Zhou; Thao M. Dang; Yuzhi Guo; Hehuan Ma; Wenliang Zhong; Saiyang Na; Jean Gao; Junzhou Huang (ISBI, 2025)

Towards Principled Learning for Re-ranking in Recommender Systems. - Qunwei Li; Linghui Li; Jianbin Lin; Wenliang Zhong (SIGIR, 2025)

MLLM4PUE: Toward Universal Embeddings in Computational Pathology through Multimodal LLMs. - Qifeng Zhou; Thao M. Dang; Wenliang Zhong; Yuzhi Guo; Hehuan Ma; Saiyang Na; Junzhou Huang (CoRR, 2025)

EmbedAgent: Benchmarking Large Language Models in Embedded System Development. - Ruiyang Xu; Jialun Cao; Mingyuan Wu; Wenliang Zhong; Yaojie Lu 001; Ben He; Xianpei Han; Shing-Chi Cheung; Le Sun 001 (CoRR, 2025)

Put Teacher in Student's Shoes: Cross-Distillation for Ultra-compact Model Compression Framework. - Maolin Wang; Jun Chu; Sicong Xie; Xiaoling Zang; Yao Zhao; Wenliang Zhong; Xiangyu Zhao (CoRR, 2025)

M^2VAE: Multi-Modal Multi-View Variational Autoencoder for Cold-start Item Recommendation. - Chuan He; Yongchao Liu; Qiang Li; Wenliang Zhong; Chuntao Hong; Xin Yao 001 (CoRR, 2025)

LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools? - Guozhao Mo; Wenliang Zhong; Jiawei Chen 011; Xuanang Chen; Yaojie Lu 001; Hongyu Lin; Ben He; Xianpei Han; Le Sun 001 (CoRR, 2025)