Jyun-Yu Jiang My Mandarin Name is ''姜俊宇''.


This is a photo taken at Hokkaido, Japan.

General Information [Curriculum Vitae] [Google Scholar] [DBLP]

I am a senior applied scientist and researcher at Amazon Search where I joined in 2021. I received my Ph.D. from Department of Computer Science at University of California, Los Angeles in 2021. Before that, I received my M.S. and B.S. degrees from Department of Computer Science and Information Engineering at National Taiwan University in 2015 and 2013.

My research interests include Machine Learning, Data Mining, Natural Language Processing, Information Retrieval, Computational Social Science, and Bioinformatics. More specifically, I am interested in developing effective machine learning techniques and efficient algorithms to solve real-world problems.

Contact Information

  • E-mail: My email address is jyunyu [AT] amazon [DOT] com or My email address is jyunyu.jiang [AT] gmail [DOT] com

Publications

2024

  • Xiusi Chen, Jyun-Yu Jiang, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu and Wei Wang. MinPrompt: Graph-based Minimal Prompt Data Augmentation for Few-shot Question Answering. In Proceedings of The 62nd Annual Meeting of the Association for Computational Linguistics (ACL '24), ACL, 2024. The preprint version is available at arXiv.
  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Entity Disambiguation with Extreme Multi-label Ranking. In Proceedings of 2024 The Web Conference (WWW '24), ACM, 2024.
  • Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Mutasem Al-Darabsah, Choon-Hui Teo, Cho-Jui Hsieh, Hsiang-Fu Yu and S. V. N. Vishwanathan. PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models. In Proceedings of The 17th ACM International Conference on Web Search and Data Mining (WSDM '24), ACM, 2024.

2023

  • Jiong Zhang, Yau-Shian Wang, Wei-Cheng Chang, Wei Li, Jyun-Yu Jiang, Cho-Jui Hsieh and Hsiang-Fu Yu. Build Faster with Less: A Journey to Accelerate Sparse Model Building for Semantic Matching in Product Search. In Proceedings of The 32nd ACM International Conference on Information and Knowledge Management (CIKM '23), ACM, 2023.
  • Hao-Lun Lin, Jyun-Yu Jiang, Ming-Hao Juan and Pu-Jen Cheng. printf: Preference Modeling Based on User Reviews with Item Images and Textual Information via Graph Learning. In Proceedings of The 32nd ACM International Conference on Information and Knowledge Management (CIKM '23), ACM, 2023.
  • Eli Chien, Jiong Zhang, Cho-Jui Hsieh, Jyun-Yu Jiang, Wei-Cheng Chang, Olgica Milenkovic and Hsiang-Fu Yu. PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation. In Proceedings of the 40th International Conference on Machine Learning (ICML '23), PMLR, 2023.
  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Uncertainty Quantification for Extreme Classification. In Proceedings of The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23), ACM, 2023. The preprint version is available at arXiv.
  • Seungbae Kim, Jyun-Yu Jiang, Jinyoung Han and Wei Wang. InfluencerRank: Discovering Effective Influencers via Graph Convolutional Attentive Recurrent Neural Networks. In The 17th International AAAI Conference on Web and Social Media (ICWSM '23), AAAI, 2023.
  • Yu Yan, Jyun-Yu Jiang, Mingzhou Fu, Ding Wang, Alexander Pelletier, Dibakar Sigdel, Wei Wang and Peipei Ping. MIND-S: A Novel Deep Learning Prediction Model For Elucidating Protein PTMs In Human Diseases. Cell Reports Methods, 2023.
  • Patrick H. Chen, Wei-Cheng Chang, Jyun-Yu Jiang, Hsiang-Fu Yu, Inderjit Dhillon and Cho-Jui Hsieh. FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. In Proceedings of 2023 The Web Conference (WWW '23), ACM, 2023.
  • Xiusi Chen, Yu Zhang, Jinliang Deng, Jyun-Yu Jiang and Wei Wang. Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation. In Proceedings of the 2023 SIAM International Conference on Data Mining (SDM '23), SIAM, 2023. Best Poster Award Honorable Mention.
  • Xiusi Chen, Jyun-Yu Jiang, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Wei Wang. MinPrompt: Graph-based Minimal Prompt Data Augmentation for Few-shot Question Answering. Technical Report, 2023.

2022

  • Hsiang-Fu Yu, Jiong Zhang, Wei-Cheng Chang, Jyun-Yu Jiang, Wei Li and Cho-Jui Hsieh. Hands-on Tutorial "PECOS: Prediction for Enormous and Correlated Output Spaces." The 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), ACM, 2022.
  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Relevance under the Iceberg: Reasonable Prediction for Extreme Multi-label Classification. In Proceedings of The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '22), ACM, 2022.
  • Xiusi Chen, Jyun-Yu Jiang, Kun Jin, Yichao Zhou, Mingyan Liu, Paul Jeffrey Brantingham and Wei Wang. ReLiable: Offline Reinforcement Learning for Tactical Strategies in Professional Basketball Games. In Proceedings of The 31st ACM International Conference on Information and Knowledge Management (CIKM '22), ACM, 2022.
  • Xiusi Chen, Jyun-Yu Jiang and Wei Wang. Scalable Graph Representation Learning via Locality-Sensitive Hashing. In Proceedings of The 31st ACM International Conference on Information and Knowledge Management (CIKM '22), ACM, 2022.
  • Jyun-Yu Jiang, Yichao Zhou, Xiusi Chen, Yan-Ru Jhou, Liqi Zhao, Sabrina Liu, Po-Chun Yang, Jule Ahmar and Wei Wang. COVID-19 Surveiller: toward a robust and effective pandemic surveillance system based on social media mining. In Philosophical Transactions of the Royal Society A, 2022.
  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Uncertainty in Extreme Multi-label Classification. Technical Report, 2022.

2021

2020

2019

2018

2017

Before 2016

Research Areas

Large-scale Machine Learning

  • Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Mutasem Al-Darabsah, Choon-Hui Teo, Cho-Jui Hsieh, Hsiang-Fu Yu and S. V. N. Vishwanathan. PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models. In Proceedings of The 17th ACM International Conference on Web Search and Data Mining (WSDM '24), ACM, 2024.
  • Jiong Zhang, Yau-Shian Wang, Wei-Cheng Chang, Wei Li, Jyun-Yu Jiang, Cho-Jui Hsieh and Hsiang-Fu Yu. Build Faster with Less: A Journey to Accelerate Sparse Model Building for Semantic Matching in Product Search In Proceedings of The 32nd ACM International Conference on Information and Knowledge Management (CIKM '23), ACM, 2023.
  • Eli Chien, Jiong Zhang, Cho-Jui Hsieh, Jyun-Yu Jiang, Wei-Cheng Chang, Olgica Milenkovic and Hsiang-Fu Yu. PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation. In Proceedings of the 40th International Conference on Machine Learning (ICML '23), PMLR, 2023.
  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Uncertainty Quantification for Extreme Classification. In Proceedings of The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23), ACM, 2023. The preprint version is available at arXiv.
  • Patrick H. Chen, Wei-Cheng Chang, Jyun-Yu Jiang, Hsiang-Fu Yu, Inderjit Dhillon and Cho-Jui Hsieh. FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. In Proceedings of 2023 The Web Conference (WWW '23), ACM, 2023.
  • Hsiang-Fu Yu, Jiong Zhang, Wei-Cheng Chang, Jyun-Yu Jiang, Wei Li and Cho-Jui Hsieh. Hands-on Tutorial "PECOS: Prediction for Enormous and Correlated Output Spaces." The 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), ACM, 2022.
  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Relevance under the Iceberg: Reasonable Prediction for Extreme Multi-label Classification. In Proceedings of The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '22), ACM, 2022.
  • Xiusi Chen, Jyun-Yu Jiang and Wei Wang. Scalable Graph Representation Learning via Locality-Sensitive Hashing. In Proceedings of The 31st ACM International Conference on Information and Knowledge Management (CIKM '22), ACM, 2022.
  • Jyun-Yu Jiang*, Patrick H. Chen*, Cho-Jui Hsieh and Wei Wang. Clustering and Constructing User Coresets to Accelerate Large-scale Top-K Recommender Systems. In Proceedings of the 2020 World Wide Web Conference (WWW '20), ACM, 2020. (*equal contribution) [slides] [code]

[back to research areas]

Information Retrieval and Web Search

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Social Media Mining

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Bioinformatics and Biomedical Informatics

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General Machine Learning Research

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Selected Awards

Problem Solving Contest

Education

2016/09 -- 2021/06

2013/09 -- 2015/07

2009/09 -- 2013/06

2006/09 -- 2009/06

Taipei Municipal Jianguo High School, Taipei, Taiwan

Diploma in Math and Science Gifted Program


Last modified at PT 05:23 05/21/2024

My email address is jyunyu.jiang [AT] gmail.com

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