LightLT: a Lightweight Representation Quantization Framework for Long-tail Data,
Haoyu Wang, Ruirui Li, Zhengyang Wang, Xianfeng Tang, Danqing Zhang, Monica Cheng, Bing Yin, Jasha Droppo, Suhang Wang, Jing Gao
[ICDE'24]40th IEEE International Conference on Data Engineering (ICDE 2024)
[paper]
Exploiting Intent Evolution in E-commercial Query Recommendation,
Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Cheng, Bing Yin, Suhang Wang, Philip S. Yu
[KDD'23]Proceedings of 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2023, applied data science paper)
[paper]
AutoGDA: Automated Graph Data Augmentation for Node Classification,
Tong Zhao, Xianfeng Tang, Danqing Zhang, Haoming Jiang, Nikhil Rao, Yiwei Song, Pallav Agrawal, Karthik Subbian, Bing Yin, Meng Jiang
[LOG'22]Learning on Graphs Conference (LOG 2022, research paper)
[paper]
Condensing Graphs via One-Step Gradient Matching
Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng li, Danqing Zhang, Jiliang Tang, Bing Yin
[KDD'22]Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2022, research paper)
[paper]
SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models
Jingfeng Yang, Haoming Jiang, Qingyu Yin, Danqing Zhang, Bing Yin, Diyi Yang
[NAACL'22 (Findings)]The 2021 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2022, long paper, findings)
[paper]
RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph
Ruijie Wang, Zheng Li, Danqing Zhang, Qingyu Yin, Tong Zhao, Bing Yin and Tarek Abdelzaher
[WWW'22]The Web Conference 2022 (WWW 2022, long paper)
[paper]
MetaTS: Meta Teacher-Student Network for Multilingual Sequence Labeling with Minimal Supervision
Zheng Li, Danqing Zhang, Tianyu Cao, Ying Wei, Yiwei Song and Bing Yin
[EMNLP'21]The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021, long paper)
[paper]
QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction
Danqing Zhang*, Zheng Li*, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao and Qiang Yang
[CIKM'21]The 30th ACM International Conference on Information and Knowledge Management (CIKM 2021, Applied Research Track)
[paper], [video], [CIKM booster video]
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data
Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin and Tuo Zhao
[ACL'21]The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021, long paper)
[paper], [code]
Improving Pretrained Models for Zero-shot Multi-label Text Classification through Reinforced Label Hierarchy Reasoning
Hui Liu, Danqing Zhang, Bing Yin, Xiaodan Zhu
[NAACL'21]The 2021 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2021, long paper)
[paper], [code]
Predicting driver attention in critical situations
Ye Xia, Danqing Zhang, Jinkyu Kim, Ken Nakayama, Karl Zipser, David Whitney
[ACCV,18]Asian conference on computer vision (ACCV), 2018
[paper], [code]
Connected population synthesis for transportation simulation
Danqing Zhang*, Junyu Cao*, Sid Feygin, Dounan Tang, Zuo-Jun Max Shen, Alexei Pozdnoukhov
[TRC'19]Transportation research part C: emerging technologies (ranks No.2 in transportation journals, h-index: 133), 2019
[paper], [code], [press]
Using machine learning to analyze air traffic management actions: Ground delay program case study
Yulin Liu, Yi Liu, Mark Hansen, Alexey Pozdnukhov, Danqing Zhang
[TRE'19]Transportation Research Part E: Logistics and Transportation Review (ranks No.7 in transportation journals, h-index: 110), 2019
[paper]
Social-enabled Urban Data Analytics
Danqing Zhang
[Thesis'18]PhD Thesis, University of California Berkeley, 2018
[paper]
US Patent No. 11,256,707, PER-QUERY DATABASE PARTITION RELEVANCE FOR SEARCH
Light Feed-Forward Networks for Shard Selection in Large-scale Product Search
Danqing Zhang*, Heran Lin*, Pengcheng Xiong*, Fan Yang, Ryoichi Kato, Mukul Kumar, William Headden, Bing Yin
[SIGIR eCom'20 best paper]43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, eCommerce Workshop, 2020
Best Paper Award
[paper], [video presentation]
GraphRAD: A Graph-based Risky Account Detection System
Danqing Zhang*, Jun Ma*, Yun Wang, Yan Zhang, Alexei Pozdnoukhov
[KDD-MLG'18]Knowledge Discovery and Data Mining (KDD) Mining and Learning with Graphs (MLG) Workshop, 2018
[paper], [code]
Modeling Ground Delay Program Incidence using Convective and Local Weather Information
Yi Liu, Mark Hansen, Danqing Zhang, Yulin Liu, Alexei Pozdnukhov
[ATM R&D'17 best paper]Twelfth USA/Europe Air Traffic Management Research and Development Seminar, 2017
Best Paper Award
[paper]
A generative model of urban activities from cellular data
Mogeng Yin, Madeleine Sheehan, Danqing Zhang, Jean-Francois Paiement, Alexei Pozdnoukhov
[KDD-LSTS'16]Knowledge Discovery and Data Mining (KDD) Machine Learning for Large Scale Transportation Systems (LSTS) Workshop, 2016
[paper], [code]
Short Text Pre-training with Extended Token Classification for E-commerce Query Understanding
Haoming Jiang, Tianyu Cao, Zheng Li, Chen Luo, Xianfeng Tang, Qingyu Yin, Danqing Zhang, Rahul Goutam, Bing Yin
[arXiv'22]Technical Report, 2022
[paper]
On Data Augmentation for Extreme Multi-label Classification
Danqing Zhang, Tao Li, Haiyang Zhang, Bing Yin
[arXiv'20]Technical Report, 2020
[paper]
Social Discrete Choice Models
Danqing Zhang*, Kimon Fountoulakis*, Junyu Cao, Michael Mahoney, Alexei Pozdnoukhov
[arXiv'17]Technical Report, 2017
[paper], [code]
Training a network to attend like human drivers saves it from common but misleading loss functions
Ye Xia, Danqing Zhang, Alexei Pozdnoukhov, Ken Nakayama, Karl Zipser, David Whitney
[arXiv'17]Technical Report, 2017
[paper]
One paper on using generative model for product attribute value extraction