A Framework of Mining Semantic Regions from Trajectories. - Chun-Ta Lu; Po-Ruey Lei; Wen-Chih Peng; Ing-Jiunn Su (DASFAA (1), 2011)

Identifying Your Customers in Social Networks. - Chun-Ta Lu; Hong-Han Shuai; Philip S. Yu (CIKM, 2014)

Inferring the impacts of social media on crowdfunding. - Chun-Ta Lu; Sihong Xie; Xiangnan Kong; Philip S. Yu (WSDM, 2014)

Online multi-view clustering with incomplete views. - Weixiang Shao; Lifang He 001; Chun-Ta Lu; Philip S. Yu (IEEE BigData, 2016)

Community detection with partially observable links and node attributes. - Xiaokai Wei; Bokai Cao; Weixiang Shao; Chun-Ta Lu; Philip S. Yu (IEEE BigData, 2016)

Interpretable and effective opinion spam detection via temporal patterns mining across websites. - Yuan Yuan 016; Sihong Xie; Chun-Ta Lu; Jie Tang 001; Philip S. Yu (IEEE BigData, 2016)

HEER: Heterogeneous graph embedding for emerging relation detection from news. - Jingyuan Zhang; Chun-Ta Lu; Mianwei Zhou; Sihong Xie; Yi Chang 001; Philip S. Yu (IEEE BigData, 2016)

Online Unsupervised Multi-view Feature Selection. - Weixiang Shao; Lifang He 001; Chun-Ta Lu; Xiaokai Wei; Philip S. Yu (ICDM, 2016)

Item Recommendation for Emerging Online Businesses. - Chun-Ta Lu; Sihong Xie; Weixiang Shao; Lifang He 001; Philip S. Yu (IJCAI, 2016)

Joint Community and Structural Hole Spanner Detection via Harmonic Modularity. - Lifang He 001; Chun-Ta Lu; Jiaqi Ma 001; Jianping Cao; Linlin Shen; Philip S. Yu (KDD, 2016)

Semi-supervised Tensor Factorization for Brain Network Analysis. - Bokai Cao; Chun-Ta Lu; Xiaokai Wei; Philip S. Yu; Alex D. Leow (ECML/PKDD (1), 2016)

Spatio-Temporal Tensor Analysis for Whole-Brain fMRI Classification. - Guixiang Ma; Lifang He 001; Chun-Ta Lu; Philip S. Yu; Linlin Shen; Ann B. Ragin (SDM, 2016)

Identifying Connectivity Patterns for Brain Diseases via Multi-side-view Guided Deep Architectures. - Jingyuan Zhang; Bokai Cao; Sihong Xie; Chun-Ta Lu; Philip S. Yu; Ann B. Ragin (SDM, 2016)

Bringing semantic structures to user intent detection in online medical queries. - Chenwei Zhang; Nan Du 001; Wei Fan 001; Yaliang Li; Chun-Ta Lu; Philip S. Yu (IEEE BigData, 2017)

Connecting emerging relationships from news via tensor factorization. - Jingyuan Zhang; Chun-Ta Lu; Bokai Cao; Yi Chang 001; Philip S. Yu (IEEE BigData, 2017)

Multi-view Clustering with Graph Embedding for Connectome Analysis. - Guixiang Ma; Lifang He 001; Chun-Ta Lu; Weixiang Shao; Philip S. Yu; Alex D. Leow; Ann B. Ragin (CIKM, 2017)

Deep and Broad Learning on Content-Aware POI Recommendation. - Fengjiao Wang; Yongzhi Qu; Lei Zheng 001; Chun-Ta Lu; Philip S. Yu (CIC, 2017)

Multi-way Multi-level Kernel Modeling for Neuroimaging Classification. - Lifang He 001; Chun-Ta Lu; Hao Ding 003; Shen Wang 005; Linlin Shen; Philip S. Yu; Ann B. Ragin (CVPR, 2017)

A Broad Learning Approach for Context-Aware Mobile Application Recommendation. - Tingting Liang; Lifang He 001; Chun-Ta Lu; Liang Chen 001; Philip S. Yu; Jian Wu 001 (ICDM, 2017)

Multi-view Graph Embedding with Hub Detection for Brain Network Analysis. - Guixiang Ma; Chun-Ta Lu; Lifang He 001; Philip S. Yu; Ann B. Ragin (ICDM, 2017)

Kernelized Support Tensor Machines. - Lifang He 001; Chun-Ta Lu; Guixiang Ma; Shen Wang 005; LinLin Shen; Philip S. Yu; Ann B. Ragin (ICML, 2017)

Structural Deep Brain Network Mining. - Shen Wang 005; Lifang He 001; Bokai Cao; Chun-Ta Lu; Philip S. Yu; Ann B. Ragin (KDD, 2017)

Collective Geographical Embedding for Geolocating Social Network Users. - Fengjiao Wang; Chun-Ta Lu; Yongzhi Qu; Philip S. Yu (PAKDD (1), 2017)

Multilinear Factorization Machines for Multi-Task Multi-View Learning. - Chun-Ta Lu; Lifang He 001; Weixiang Shao; Bokai Cao; Philip S. Yu (WSDM, 2017)

Learning from Multi-View Structural Data via Structural Factorization Machines. - Chun-Ta Lu; Lifang He 001; Hao Ding 003; Philip S. Yu (CoRR, 2017)

A Self-Organizing Tensor Architecture for Multi-view Clustering. - Lifang He 001; Chun-Ta Lu; Yong Chen 016; Jiawei Zhang 001; Linlin Shen; Philip S. Yu; Fei Wang 001 (ICDM, 2018)

Spectral collaborative filtering. - Lei Zheng 001; Chun-Ta Lu; Fei Jiang; Jiawei Zhang 001; Philip S. Yu (RecSys, 2018)

Learning from Multi-View Multi-Way Data via Structural Factorization Machines. - Chun-Ta Lu; Lifang He 001; Hao Ding 003; Bokai Cao; Philip S. Yu (WWW, 2018)

MARS: Memory Attention-Aware Recommender System. - Lei Zheng 001; Chun-Ta Lu; Lifang He 001; Sihong Xie; Vahid Noroozi; He Huang 008; Philip S. Yu (CoRR, 2018)

Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks. - Jiahao Liu; Guixiang Ma; Fei Jiang; Chun-Ta Lu; Philip S. Yu; Ann B. Ragin (IEEE BigData, 2019)

Inferring Context from Pixels for Multimodal Image Classification. - Manan Shah; Krishnamurthy Viswanathan; Chun-Ta Lu; Ariel Fuxman; Zhen Li 028; Aleksei Timofeev; Chao Jia; Chen Sun 002 (CIKM, 2019)

MARS: Memory Attention-Aware Recommender System. - Lei Zheng 001; Chun-Ta Lu; Lifang He 001; Sihong Xie; He Huang 008; Chaozhuo Li; Vahid Noroozi; Bowen Dong; Philip S. Yu (DSAA, 2019)

Gated Spectral Units: Modeling Co-evolving Patterns for Sequential Recommendation. - Lei Zheng 001; Ziwei Fan 001; Chun-Ta Lu; Jiawei Zhang 001; Philip S. Yu (SIGIR, 2019)

Deep Distribution Network: Addressing the Data Sparsity Issue for Top-N Recommendation. - Lei Zheng 001; Chaozhuo Li; Chun-Ta Lu; Jiawei Zhang 001; Philip S. Yu (SIGIR, 2019)

Graph-RISE: Graph-Regularized Image Semantic Embedding. - Da-Cheng Juan; Chun-Ta Lu; Zhen Li 028; Futang Peng; Aleksei Timofeev; Yi-Ting Chen; Yaxi Gao; Tom Duerig; Andrew Tomkins; Sujith Ravi (CoRR, 2019)

MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing. - Tao Zhang 055; Congying Xia; Chun-Ta Lu; Philip S. Yu (COLING, 2020)

Neural Structured Learning: Training Neural Networks with Structured Signals. - Arjun Gopalan; Da-Cheng Juan; Cesar Ilharco Magalhaes; Chun-Sung Ferng; Allan Heydon; Chun-Ta Lu; Philip Pham; George Yu (KDD, 2020)

Ultra Fine-Grained Image Semantic Embedding. - Da-Cheng Juan; Chun-Ta Lu; Zhen Li 028; Futang Peng; Aleksei Timofeev; Yi-Ting Chen; Yaxi Gao; Tom Duerig; Andrew Tomkins; Sujith Ravi (WSDM, 2020)

CAMAR: a broad learning based context-aware recommender for mobile applications. - Tingting Liang; Lifang He 001; Chun-Ta Lu; Liang Chen 001; Haochao Ying; Philip S. Yu; Jian Wu 001 (Knowl. Inf. Syst., 2020)

Neural Structured Learning: Training Neural Networks with Structured Signals. - Arjun Gopalan; Da-Cheng Juan; Cesar Ilharco Magalhaes; Chun-Sung Ferng; Allan Heydon; Chun-Ta Lu; Philip Pham; George Yu; Yicheng Fan; Yueqi Wang (WSDM, 2021)

CARLS: Cross-platform Asynchronous Representation Learning System. - Chun-Ta Lu; Yun Zeng; Da-Cheng Juan; Yicheng Fan; Zhe Li; Jan Dlabal; Yi-Ting Chen; Arjun Gopalan; Allan Heydon; Chun-Sung Ferng; Reah Miyara; Ariel Fuxman; et al. (CoRR, 2021)

Agile Modeling: From Concept to Classifier in Minutes. - Otilia Stretcu; Edward Vendrow; Kenji Hata; Krishnamurthy Viswanathan; Vittorio Ferrari; Sasan Tavakkol; Wenlei Zhou; Aditya Avinash; Enming Luo; Neil Gordon Alldrin; MohammadHossein Bateni; Gabriel Berger; et al. (ICCV, 2023)

Benchmarking Robustness to Adversarial Image Obfuscations. - Florian Stimberg; Ayan Chakrabarti; Chun-Ta Lu; Hussein Hazimeh 001; Otilia Stretcu; Wei Qiao; Yintao Liu; Merve Kaya; Cyrus Rashtchian; Ariel Fuxman; Mehmet Tek; Sven Gowal (NeurIPS, 2023)

Agile Modeling: Image Classification with Domain Experts in the Loop. - Otilia Stretcu; Edward Vendrow; Kenji Hata; Krishnamurthy Viswanathan; Vittorio Ferrari; Sasan Tavakkol; Wenlei Zhou; Aditya Avinash; Enming Luo; Neil Gordon Alldrin; MohammadHossein Bateni; Gabriel Berger; et al. (CoRR, 2023)

Non-Intrusive Adaptation: Input-Centric Parameter-efficient Fine-Tuning for Versatile Multimodal Modeling. - Yaqing Wang 007; Jialin Wu; Tanmaya Dabral; Jiageng Zhang; Geoff Brown; Chun-Ta Lu; Frederick Liu; Yi Liang; Bo Pang 001; Michael Bendersky; Radu Soricut (CoRR, 2023)

Visual Program Distillation: Distilling Tools and Programmatic Reasoning into Vision-Language Models. - Yushi Hu; Otilia Stretcu; Chun-Ta Lu; Krishnamurthy Viswanathan; Kenji Hata; Enming Luo; Ranjay Krishna; Ariel Fuxman (CVPR, 2024)

Modeling Collaborator: Enabling Subjective Vision Classification with Minimal Human Effort via LLM Tool-Use. - Imad Eddine Toubal; Aditya Avinash; Neil Gordon Alldrin; Jan Dlabal; Wenlei Zhou; Enming Luo; Otilia Stretcu; Hao Xiong; Chun-Ta Lu; Howard Zhou; Ranjay Krishna; Ariel Fuxman; et al. (CVPR, 2024)

Scaling Up LLM Reviews for Google Ads Content Moderation. - Wei Qiao; Tushar Dogra; Otilia Stretcu; Yu-Han Lyu; Tiantian Fang; Dongjin Kwon; Chun-Ta Lu; Enming Luo; Yuan Wang 049; Chih-Chun Chia; Ariel Fuxman; Fangzhou Wang; et al. (WSDM, 2024)

S2Vec: Self-Supervised Geospatial Embeddings. - Shushman Choudhury; Elad Aharoni; Chandrakumari Suvarna; Iveel Tsogsuren; Abdul Rahman Kreidieh; Chun-Ta Lu; Neha Arora (CoRR, 2025)