Yu, Philip S.

119 publications

NeurIPS 2025 AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees Yangning Li, Shaoshen Chen, Yinghui Li, Yankai Chen, Hai-Tao Zheng, Hui Wang, Wenhao Jiang, Philip S. Yu

NeurIPS 2025 Atomic Thinking of LLMs: Decoupling and Exploring Mathematical Reasoning Abilities Jiayi Kuang, Haojing Huang, Yinghui Li, Xinnian Liang, Zhikun Xu, Yangning Li, Xiaoyu Tan, Chao Qu, Meishan Zhang, Ying Shen, Philip S. Yu

ICLR 2025 BANGS: Game-Theoretic Node Selection for Graph Self-Training Fangxin Wang, Kay Liu, Sourav Medya, Philip S. Yu

ICLR 2025 Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-Adaptive Planning Agent Yangning Li, Yinghui Li, Xinyu Wang, Yong Jiang, Zhen Zhang, Xinran Zheng, Hui Wang, Hai-Tao Zheng, Fei Huang, Jingren Zhou, Philip S. Yu

ICLRW 2025 Can LLM Watermarking Robustly Prevent Unauthorized Knowledge Distillation? Leyi Pan, Aiwei Liu, Shiyu Huang, Yijian Lu, Xuming Hu, Lijie Wen, Irwin King, Philip S. Yu

ICLR 2025 Can Watermarked LLMs Be Identified by Users via Crafted Prompts? Aiwei Liu, Sheng Guan, Yiming Liu, Leyi Pan, Yifei Zhang, Liancheng Fang, Lijie Wen, Philip S. Yu, Xuming Hu

LoG 2025 Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Models Kay Liu, Hengrui Zhang, Ziqing Hu, Fangxin Wang, Philip S. Yu

NeurIPS 2025 Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models Li Sun, Zhenhao Huang, Ming Zhang, Philip S. Yu

ICLR 2025 DiffPuter: Empowering Diffusion Models for Missing Data Imputation Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu

NeurIPS 2025 Dynamic Bundling with Large Language Models for Zero-Shot Inference on Text-Attributed Graphs Yusheng Zhao, Qixin Zhang, Xiao Luo, Weizhi Zhang, Zhiping Xiao, Wei Ju, Philip S. Yu, Ming Zhang

NeurIPS 2025 Embracing Trustworthy Brain-Agent Collaboration as Paradigm Extension for Intelligent Assistive Technologies Yankai Chen, Xinni Zhang, Yifei Zhang, Yangning Li, Henry Peng Zou, Chunyu Miao, Weizhi Zhang, Xue Liu, Philip S. Yu

TMLR 2025 Enhancing Fairness in Unsupervised Graph Anomaly Detection Through Disentanglement Wenjing Chang, Kay Liu, Philip S. Yu, Jianjun Yu

ICLRW 2025 ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models via Error Detection Yibo Yan, Shen Wang, Jiahao Huo, Hang Li, Boyan Li, Jiamin Su, Xiong Gao, YiFan Zhang, Tianlong Xu, Zhendong Chu, Aoxiao Zhong, Kun Wang, Hui Xiong, Philip S. Yu, Xuming Hu, Qingsong Wen

NeurIPS 2025 GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-Tuning Haonan Yuan, Qingyun Sun, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu

NeurIPS 2025 Glocal Information Bottleneck for Time Series Imputation Jie Yang, Kexin Zhang, Guibin Zhang, Philip S. Yu, Kaize Ding

ICML 2025 How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees Haonan Yuan, Qingyun Sun, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu

ICLR 2025 IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning Jiawen Qin, Haonan Yuan, Qingyun Sun, Lyujin Xu, Jiaqi Yuan, Pengfeng Huang, Zhaonan Wang, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu

TMLR 2025 LEGO-Learn: Label-Efficient Graph Open-Set Learning Haoyan Xu, Kay Liu, Zhengtao Yao, Philip S. Yu, Mengyuan Li, Kaize Ding, Yue Zhao

ICML 2025 One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs Yinghui Li, Jiayi Kuang, Haojing Huang, Zhikun Xu, Xinnian Liang, Yi Yu, Wenlian Lu, Yangning Li, Xiaoyu Tan, Chao Qu, Ying Shen, Hai-Tao Zheng, Philip S. Yu

IJCAI 2025 Out-of-Distribution Detection by Regaining Lost Clues (Abstract Reprint) Zhilin Zhao, Longbing Cao, Philip S. Yu

AAAI 2025 Pioneer: Physics-Informed Riemannian Graph ODE for Entropy-Increasing Dynamics Li Sun, Ziheng Zhang, Zixi Wang, Yujie Wang, Qiqi Wan, Hao Li, Hao Peng, Philip S. Yu

ICLRW 2025 RINTAW: A Robust Invisible Watermark for Tabular Generative Models Liancheng Fang, Aiwei Liu, Henry Peng Zou, Hengrui Zhang, Philip S. Yu

ICLR 2025 Refine Knowledge of Large Language Models via Adaptive Contrastive Learning Yinghui Li, Haojing Huang, Jiayi Kuang, Yangning Li, Shu-Yu Guo, Chao Qu, Xiaoyu Tan, Hai-Tao Zheng, Ying Shen, Philip S. Yu

NeurIPS 2025 Robust Graph Condensation via Classification Complexity Mitigation Jiayi Luo, Qingyun Sun, Beining Yang, Haonan Yuan, Xingcheng Fu, Yanbiao Ma, Jianxin Li, Philip S. Yu

ICML 2025 SDMG: Smoothing Your Diffusion Models for Powerful Graph Representation Learning Junyou Zhu, Langzhou He, Chao Gao, Dongpeng Hou, Zhen Su, Philip S. Yu, Juergen Kurths, Frank Hellmann

NeurIPS 2025 SSRB: Direct Natural Language Querying to Massive Heterogeneous Semi-Structured Data Xin Zhang, Mingxin Li, Yanzhao Zhang, Dingkun Long, Yongqi Li, Yinghui Li, Pengjun Xie, Meishan Zhang, Wenjie Li, Min Zhang, Philip S. Yu

NeurIPS 2025 Seeking and Updating with Live Visual Knowledge Mingyang Fu, Yuyang Peng, Dongping Chen, Zetong Zhou, Benlin Liu, Yao Wan, Zhou Zhao, Philip S. Yu, Ranjay Krishna

AAAI 2025 Structural Entropy Guided Probabilistic Coding Xiang Huang, Hao Peng, Li Sun, Hui Lin, Chunyang Liu, Jiang Cao, Philip S. Yu

IJCAI 2025 T-T: Table Transformer for Tagging-Based Aspect Sentiment Triplet Extraction Kun Peng, Chaodong Tong, Cong Cao, Hao Peng, Qian Li, Guanlin Wu, Lei Jiang, Yanbing Liu, Philip S. Yu

ICLR 2025 TIS-DPO: Token-Level Importance Sampling for Direct Preference Optimization with Estimated Weights Aiwei Liu, Haoping Bai, Zhiyun Lu, Yanchao Sun, Xiang Kong, Xiaoming Simon Wang, Jiulong Shan, Albin Madappally Jose, Xiaojiang Liu, Lijie Wen, Philip S. Yu, Meng Cao

ICML 2025 TabNAT: A Continuous-Discrete Joint Generative Framework for Tabular Data Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu

NeurIPS 2025 Topology-Aware Conformal Prediction for Stream Networks Jifan Zhang, Fangxin Wang, Zihe Song, Philip S. Yu, Kaize Ding, Shixiang Zhu

AAAI 2025 Towards Effective, Efficient and Unsupervised Social Event Detection in the Hyperbolic Space Xiaoyan Yu, Yifan Wei, Shuaishuai Zhou, Zhiwei Yang, Li Sun, Hao Peng, Liehuang Zhu, Philip S. Yu

IJCAI 2025 Trace: Structural Riemannian Bridge Matching for Transferable Source Localization in Information Propagation Li Sun, Suyang Zhou, Bowen Fang, Hechuan Zhang, Junda Ye, Yutong Ye, Philip S. Yu

AAAI 2024 Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering Jingyu Pu, Chenhang Cui, Xinyue Chen, Yazhou Ren, Xiaorong Pu, Zhifeng Hao, Philip S. Yu, Lifang He

ICLR 2024 An Unforgeable Publicly Verifiable Watermark for Large Language Models Aiwei Liu, Leyi Pan, Xuming Hu, Shuang Li, Lijie Wen, Irwin King, Philip S. Yu

NeurIPSW 2024 Beyond Directed Acyclic Computation Graph with Cyclic Neural Network Liangwei Yang, Hengrui Zhang, Weizhi Zhang, Zihe Song, Jing Ma, Jiawei Zhang, Philip S. Yu

AAAI 2024 Dual-Channel Learning Framework for Drug-Drug Interaction Prediction via Relation-Aware Heterogeneous Graph Transformer Xiaorui Su, Pengwei Hu, Zhu-Hong You, Philip S. Yu, Lun Hu

NeurIPS 2024 GC-Bench: An Open and Unified Benchmark for Graph Condensation Qingyun Sun, Ziying Chen, Beining Yang, Cheng Ji, Xingcheng Fu, Sheng Zhou, Hao Peng, Jianxin Li, Philip S. Yu

IJCAI 2024 Graph Neural Networks for Brain Graph Learning: A Survey Xuexiong Luo, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Quan Z. Sheng, David McAlpine, Paul F. Sowman, Alexis Giral, Philip S. Yu

AAAI 2024 Hierarchical and Incremental Structural Entropy Minimization for Unsupervised Social Event Detection Yuwei Cao, Hao Peng, Zhengtao Yu, Philip S. Yu

ICML 2024 LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering Li Sun, Zhenhao Huang, Hao Peng, Yujie Wang, Chunyang Liu, Philip S. Yu

AAAI 2024 Motif-Aware Riemannian Graph Neural Network with Generative-Contrastive Learning Li Sun, Zhenhao Huang, Zixi Wang, Feiyang Wang, Hao Peng, Philip S. Yu

UAI 2024 Multi-Relational Structural Entropy Yuwei Cao, Hao Peng, Angsheng Li, Chenyu You, Zhifeng Hao, Philip S. Yu

ICML 2024 Position: TrustLLM: Trustworthiness in Large Language Models Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Yang Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao

MLOSS 2024 PyGOD: A Python Library for Graph Outlier Detection Kay Liu, Yingtong Dou, Xueying Ding, Xiyang Hu, Ruitong Zhang, Hao Peng, Lichao Sun, Philip S. Yu

NeurIPS 2024 Spiking Graph Neural Network on Riemannian Manifolds Li Sun, Zhenhao Huang, Qiqi Wan, Hao Peng, Philip S. Yu

NeurIPSW 2024 TABGEN-RAG: Iterative Retrieval for Tabular Data Generation with Large Language Models Liancheng Fang, Aiwei Liu, Hengrui Zhang, Henry Peng Zou, Weizhi Zhang, Philip S. Yu

AAAI 2024 Three Heads Are Better than One: Improving Cross-Domain NER with Progressive Decomposed Network Xuming Hu, Zhaochen Hong, Yong Jiang, Zhichao Lin, Xiaobin Wang, Pengjun Xie, Philip S. Yu

ICLR 2024 Towards Understanding Factual Knowledge of Large Language Models Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen, Philip S. Yu, Zhijiang Guo

TMLR 2024 Uncertainty in Graph Neural Networks: A Survey Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu

NeurIPS 2024 When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models Yinghui Li, Qingyu Zhou, Yuanzhen Luo, Shirong Ma, Yangning Li, Hai-Tao Zheng, Xuming Hu, Philip S. Yu

IJCAI 2023 CONGREGATE: Contrastive Graph Clustering in Curvature Spaces Li Sun, Feiyang Wang, Junda Ye, Hao Peng, Philip S. Yu

NeurIPS 2023 Equal Opportunity of Coverage in Fair Regression Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S Yu

IJCAI 2023 Hierarchical State Abstraction Based on Structural Information Principles Xianghua Zeng, Hao Peng, Angsheng Li, Chunyang Liu, Lifang He, Philip S. Yu

AAAI 2023 Learning to Select from Multiple Options Jiangshu Du, Wenpeng Yin, Congying Xia, Philip S. Yu

AAAI 2023 Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu

AAAI 2023 Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces Li Sun, Junda Ye, Hao Peng, Feiyang Wang, Philip S. Yu

AAAI 2022 A Self-Supervised Mixed-Curvature Graph Neural Network Li Sun, Zhongbao Zhang, Junda Ye, Hao Peng, Jiawei Zhang, Sen Su, Philip S. Yu

NeurIPS 2022 BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H Chen, Zhihao Jia, Philip S Yu

AAAI 2022 Graph Structure Learning with Variational Information Bottleneck Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu

NeurIPS 2022 Rethinking and Scaling up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination Yizhen Zheng, Shirui Pan, Vincent CS Lee, Yu Zheng, Philip S Yu

NeurIPS 2021 From Canonical Correlation Analysis to Self-Supervised Graph Neural Networks Hengrui Zhang, Qitian Wu, Junchi Yan, David P. Wipf, Philip S Yu

IJCAI 2021 Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks Gongxu Luo, Jianxin Li, Hao Peng, Carl Yang, Lichao Sun, Philip S. Yu, Lifang He

IJCAI 2021 Graph Learning Based Recommender Systems: A Review Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Francesco Ricci, Philip S. Yu

AAAI 2021 Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng, Sen Su, Philip S. Yu

AAAI 2021 KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning Ye Liu, Yao Wan, Lifang He, Hao Peng, Philip S. Yu

IJCAI 2020 Adversarial Mutual Information Learning for Network Embedding Dongxiao He, Lu Zhai, Zhigang Li, Di Jin, Liang Yang, Yuxiao Huang, Philip S. Yu

IJCAI 2020 Deep Learning for Community Detection: Progress, Challenges and Opportunities Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Jian Yang, Philip S. Yu

IJCAI 2020 Entity Synonym Discovery via Multipiece Bilateral Context Matching Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu

AAAI 2019 Adversarial Learning for Weakly-Supervised Social Network Alignment Chaozhuo Li, Senzhang Wang, Yukun Wang, Philip S. Yu, Yanbo Liang, Yun Liu, Zhoujun Li

AAAI 2019 DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System Zhi-Hong Deng, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu

IJCAI 2019 Fine-Grained Event Categorization with Heterogeneous Graph Convolutional Networks Hao Peng, Jianxin Li, Qiran Gong, Yangqiu Song, Yuanxing Ning, Kunfeng Lai, Philip S. Yu

IJCAI 2019 Heterogeneous Graph Matching Networks for Unknown Malware Detection Shen Wang, Zhengzhang Chen, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang, Jiaping Gui, Zhichun Li, Haifeng Chen, Philip S. Yu

IJCAI 2019 Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization Mehrnaz Najafi, Lifang He, Philip S. Yu

AAAI 2019 Private Model Compression via Knowledge Distillation Ji Wang, Weidong Bao, Lichao Sun, Xiaomin Zhu, Bokai Cao, Philip S. Yu

IJCAI 2018 Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks Xiaotian Han, Chuan Shi, Senzhang Wang, Philip S. Yu, Li Song

AAAI 2018 Dual Attention Network for Product Compatibility and Function Satisfiability Analysis Hu Xu, Sihong Xie, Lei Shu, Philip S. Yu

IJCAI 2018 Lifelong Domain Word Embedding via Meta-Learning Hu Xu, Bing Liu, Lei Shu, Philip S. Yu

AAAI 2018 Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis Ye Liu, Lifang He, Bokai Cao, Philip S. Yu, Ann B. Ragin, Alex D. Leow

ICML 2018 PredRNN++: Towards a Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning Yunbo Wang, Zhifeng Gao, Mingsheng Long, Jianmin Wang, Philip S Yu

ICCV 2017 HashNet: Deep Learning to Hash by Continuation Zhangjie Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu

ICML 2017 Kernelized Support Tensor Machines Lifang He, Chun-Ta Lu, Guixiang Ma, Shen Wang, Linlin Shen, Philip S. Yu, Ann B. Ragin

NeurIPS 2017 Learning Multiple Tasks with Multilinear Relationship Networks Mingsheng Long, Zhangjie Cao, Jianmin Wang, Philip S Yu

CVPR 2017 Multi-Way Multi-Level Kernel Modeling for Neuroimaging Classification Lifang He, Chun-Ta Lu, Hao Ding, Shen Wang, Linlin Shen, Philip S. Yu, Ann B. Ragin

NeurIPS 2017 PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs Yunbo Wang, Mingsheng Long, Jianmin Wang, Zhifeng Gao, Philip S Yu

ECML-PKDD 2017 Rethinking Unsupervised Feature Selection: From Pseudo Labels to Pseudo Must-Links Xiaokai Wei, Sihong Xie, Bokai Cao, Philip S. Yu

IJCAI 2017 SEVEN: Deep Semi-Supervised Verification Networks Vahid Noroozi, Lei Zheng, Sara Bahaadini, Sihong Xie, Philip S. Yu

ECML-PKDD 2017 Sequential Keystroke Behavioral Biometrics for Mobile User Identification via Multi-View Deep Learning Lichao Sun, Yuqi Wang, Bokai Cao, Philip S. Yu, Witawas Srisa-an, Alex D. Leow

CVPR 2017 Spatiotemporal Pyramid Network for Video Action Recognition Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu

IJCAI 2016 Causality Based Propagation History Ranking in Social Networks Zheng Wang, Chaokun Wang, Jisheng Pei, Xiaojun Ye, Philip S. Yu

ECML-PKDD 2016 Enhancing Traffic Congestion Estimation with Social Media by Coupled Hidden Markov Model Senzhang Wang, Fengxiang Li, Leon Stenneth, Philip S. Yu

IJCAI 2016 Item Recommendation for Emerging Online Businesses Chun-Ta Lu, Sihong Xie, Weixiang Shao, Lifang He, Philip S. Yu

ECML-PKDD 2016 Multi-Graph Clustering Based on Interior-Node Topology with Applications to Brain Networks Guixiang Ma, Lifang He, Bokai Cao, Jiawei Zhang, Philip S. Yu, Ann B. Ragin

ECML-PKDD 2016 Semi-Supervised Tensor Factorization for Brain Network Analysis Bokai Cao, Chun-Ta Lu, Xiaokai Wei, Philip S. Yu, Alex D. Leow

ECML-PKDD 2016 Trust Hole Identification in Signed Networks Jiawei Zhang, Qianyi Zhan, Lifang He, Charu C. Aggarwal, Philip S. Yu

IJCAI 2016 Understanding Information Diffusion Under Interactions Yuan Su, Xi Zhang, Philip S. Yu, Wen Hua, Xiaofang Zhou, Binxing Fang

AISTATS 2016 Unsupervised Feature Selection by Preserving Stochastic Neighbors Xiaokai Wei, Philip S. Yu

AAAI 2016 Unsupervised Feature Selection on Networks: A Generative View Xiaokai Wei, Bokai Cao, Philip S. Yu

AAAI 2015 Burst Time Prediction in Cascades Senzhang Wang, Zhao Yan, Xia Hu, Philip S. Yu, Zhoujun Li

ECML-PKDD 2015 Discovering Audience Groups and Group-Specific Influencers Shuyang Lin, Qingbo Hu, Jingyuan Zhang, Philip S. Yu

IJCAI 2015 Integrated Anchor and Social Link Predictions Across Social Networks Jiawei Zhang, Philip S. Yu

ECML-PKDD 2015 Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with L2, 1 Regularization Weixiang Shao, Lifang He, Philip S. Yu

CVPR 2014 Transfer Joint Matching for Unsupervised Domain Adaptation Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu

AAAI 2013 Towards Cohesive Anomaly Mining Yun Xiong, Yangyong Zhu, Philip S. Yu, Jian Pei

ICCV 2013 Transfer Feature Learning with Joint Distribution Adaptation Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu

CVPR 2013 Transfer Sparse Coding for Robust Image Representation Mingsheng Long, Guiguang Ding, Jianmin Wang, Jiaguang Sun, Yuchen Guo, Philip S. Yu

ECML-PKDD 2011 Multi-Label Ensemble Learning Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang

IJCAI 2009 Early Prediction on Time Series: A Nearest Neighbor Approach Zhengzheng Xing, Jian Pei, Philip S. Yu

AAAI 2008 Clustering on Complex Graphs Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu, Tianbing Xu

ECML-PKDD 2008 Hierarchical, Parameter-Free Community Discovery Spiros Papadimitriou, Jimeng Sun, Christos Faloutsos, Philip S. Yu

AAAI 2007 Graph Partitioning Based on Link Distributions Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu

ICML 2007 Relational Clustering by Symmetric Convex Coding Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip S. Yu

AAAI 2006 Classification Spanning Private Databases Ke Wang, Yabo Xu, Rong She, Philip S. Yu

ICML 2006 Spectral Clustering for Multi-Type Relational Data Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip S. Yu

AAAI 2004 Text Classification by Labeling Words Bing Liu, Xiaoli Li, Wee Sun Lee, Philip S. Yu

IJCAI 2003 Inductive Learning in Less than One Sequential Data Scan Wei Fan, Haixun Wang, Philip S. Yu, Shaw-Hwa Lo

ICML 2002 Partially Supervised Classification of Text Documents Bing Liu, Wee Sun Lee, Philip S. Yu, Xiaoli Li

AAAI 2002 Pruning and Dynamic Scheduling of Cost-Sensitive Ensembles Wei Fan, Fang Chu, Haixun Wang, Philip S. Yu