Chun-Ta Lu

According to our database, Chun-Ta Lu authored at least 48 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

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, Chih-Chun Chia, Ariel Fuxman, Fangzhou Wang, Ranjay Krishna, Mehmet Tek

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 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, Tom Duerig

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Non-Intrusive Adaptation: Input-Centric Parameter-efficient Fine-Tuning for Versatile Multimodal Modeling.

Yaqing Wang, Jialin Wu, Tanmaya Dabral, Jiageng Zhang, Geoff Brown, Chun-Ta Lu, Frederick Liu, Yi Liang, Bo Pang, Michael Bendersky, Radu Soricut

CoRR, 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, Andrew Bunner, Chun-Ta Lu, Javier A Rey, Ariel Fuxman

CoRR, 2023

Benchmarking Robustness to Adversarial Image Obfuscations.

Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu, Hussein Hazimeh, Otilia Stretcu, Wei Qiao, Yintao Liu, Merve Kaya, Cyrus Rashtchian, Ariel Fuxman, Mehmet Tek, Sven Gowal

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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, Andrew Bunner, Chun-Ta Lu, Javier A Rey, Giulia DeSalvo, Ranjay Krishna, Ariel Fuxman

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

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, Futang Peng, Zhen Li, Tom Duerig, Andrew Tomkins

CoRR, 2021

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

Proceedings of the WSDM '21, 2021

2020

CAMAR: a broad learning based context-aware recommender for mobile applications.

Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Haochao Ying, Philip S. Yu, Jian Wu

Knowl. Inf. Syst., 2020

Ultra Fine-Grained Image Semantic Embedding.

Da-Cheng Juan, Chun-Ta Lu, Zhen Li, Futang Peng, Aleksei Timofeev, Yi-Ting Chen, Yaxi Gao, Tom Duerig, Andrew Tomkins, Sujith Ravi

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 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

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing.

Tao Zhang, Congying Xia, Chun-Ta Lu, Philip S. Yu

Proceedings of the 28th International Conference on Computational Linguistics, 2020

2019

Graph-RISE: Graph-Regularized Image Semantic Embedding.

Da-Cheng Juan, Chun-Ta Lu, Zhen Li, Futang Peng, Aleksei Timofeev, Yi-Ting Chen, Yaxi Gao, Tom Duerig, Andrew Tomkins, Sujith Ravi

CoRR, 2019

Deep Distribution Network: Addressing the Data Sparsity Issue for Top-N Recommendation.

Lei Zheng, Chaozhuo Li, Chun-Ta Lu, Jiawei Zhang, Philip S. Yu

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Gated Spectral Units: Modeling Co-evolving Patterns for Sequential Recommendation.

Lei Zheng, Ziwei Fan, Chun-Ta Lu, Jiawei Zhang, Philip S. Yu

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

MARS: Memory Attention-Aware Recommender System.

Lei Zheng, Chun-Ta Lu, Lifang He, Sihong Xie, He Huang, Chaozhuo Li, Vahid Noroozi, Bowen Dong, Philip S. Yu

Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 2019

Inferring Context from Pixels for Multimodal Image Classification.

Manan Shah, Krishnamurthy Viswanathan, Chun-Ta Lu, Ariel Fuxman, Zhen Li, Aleksei Timofeev, Chao Jia, Chen Sun

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

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

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

MARS: Memory Attention-Aware Recommender System.

Lei Zheng, Chun-Ta Lu, Lifang He, Sihong Xie, Vahid Noroozi, He Huang, Philip S. Yu

CoRR, 2018

Learning from Multi-View Multi-Way Data via Structural Factorization Machines.

Chun-Ta Lu, Lifang He, Hao Ding, Bokai Cao, Philip S. Yu

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Spectral collaborative filtering.

Lei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang, Philip S. Yu

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

A Self-Organizing Tensor Architecture for Multi-view Clustering.

Lifang He, Chun-Ta Lu, Yong Chen, Jiawei Zhang, Linlin Shen, Philip S. Yu, Fei Wang

Proceedings of the IEEE International Conference on Data Mining, 2018

2017

Learning from Multi-View Structural Data via Structural Factorization Machines.

Chun-Ta Lu, Lifang He, Hao Ding, Philip S. Yu

CoRR, 2017

Multilinear Factorization Machines for Multi-Task Multi-View Learning.

Chun-Ta Lu, Lifang He, Weixiang Shao, Bokai Cao, Philip S. Yu

Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Collective Geographical Embedding for Geolocating Social Network Users.

Fengjiao Wang, Chun-Ta Lu, Yongzhi Qu, Philip S. Yu

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

Structural Deep Brain Network Mining.

Shen Wang, Lifang He, Bokai Cao, Chun-Ta Lu, Philip S. Yu, Ann B. Ragin

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Kernelized Support Tensor Machines.

Lifang He, Chun-Ta Lu, Guixiang Ma, Shen Wang, LinLin Shen, Philip S. Yu, Ann B. Ragin

Proceedings of the 34th International Conference on Machine Learning, 2017

Multi-view Graph Embedding with Hub Detection for Brain Network Analysis.

Guixiang Ma, Chun-Ta Lu, Lifang He, Philip S. Yu, Ann B. Ragin

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

A Broad Learning Approach for Context-Aware Mobile Application Recommendation.

Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Philip S. Yu, Jian Wu

Proceedings of the 2017 IEEE International Conference on Data Mining, 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

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Deep and Broad Learning on Content-Aware POI Recommendation.

Fengjiao Wang, Yongzhi Qu, Lei Zheng, Chun-Ta Lu, Philip S. Yu

Proceedings of the 3rd IEEE International Conference on Collaboration and Internet Computing, 2017

Multi-view Clustering with Graph Embedding for Connectome Analysis.

Guixiang Ma, Lifang He, Chun-Ta Lu, Weixiang Shao, Philip S. Yu, Alex D. Leow, Ann B. Ragin

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Connecting emerging relationships from news via tensor factorization.

Jingyuan Zhang, Chun-Ta Lu, Bokai Cao, Yi Chang, Philip S. Yu

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

Bringing semantic structures to user intent detection in online medical queries.

Chenwei Zhang, Nan Du, Wei Fan, Yaliang Li, Chun-Ta Lu, Philip S. Yu

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

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

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Spatio-Temporal Tensor Analysis for Whole-Brain fMRI Classification.

Guixiang Ma, Lifang He, Chun-Ta Lu, Philip S. Yu, Linlin Shen, Ann B. Ragin

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Semi-supervised Tensor Factorization for Brain Network Analysis.

Bokai Cao, Chun-Ta Lu, Xiaokai Wei, Philip S. Yu, Alex D. Leow

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Joint Community and Structural Hole Spanner Detection via Harmonic Modularity.

Lifang He, Chun-Ta Lu, Jiaqi Ma, Jianping Cao, Linlin Shen, Philip S. Yu

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Item Recommendation for Emerging Online Businesses.

Chun-Ta Lu, Sihong Xie, Weixiang Shao, Lifang He, Philip S. Yu

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Online Unsupervised Multi-view Feature Selection.

Weixiang Shao, Lifang He, Chun-Ta Lu, Xiaokai Wei, Philip S. Yu

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

HEER: Heterogeneous graph embedding for emerging relation detection from news.

Jingyuan Zhang, Chun-Ta Lu, Mianwei Zhou, Sihong Xie, Yi Chang, Philip S. Yu

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Interpretable and effective opinion spam detection via temporal patterns mining across websites.

Yuan Yuan, Sihong Xie, Chun-Ta Lu, Jie Tang, Philip S. Yu

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Community detection with partially observable links and node attributes.

Xiaokai Wei, Bokai Cao, Weixiang Shao, Chun-Ta Lu, Philip S. Yu

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Online multi-view clustering with incomplete views.

Weixiang Shao, Lifang He, Chun-Ta Lu, Philip S. Yu

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2014

Inferring the impacts of social media on crowdfunding.

Chun-Ta Lu, Sihong Xie, Xiangnan Kong, Philip S. Yu

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Identifying Your Customers in Social Networks.

Chun-Ta Lu, Hong-Han Shuai, Philip S. Yu

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

2011

A Framework of Mining Semantic Regions from Trajectories.

Chun-Ta Lu, Po-Ruey Lei, Wen-Chih Peng, Ing-Jiunn Su

Proceedings of the Database Systems for Advanced Applications, 2011