Weijie Bian

Orcid: 0009-0009-2515-1300

According to our database1, Weijie Bian authored at least 12 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Practice on Effectively Extracting NLP Features for Click-Through Rate Prediction.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
CAN: Feature Co-Action Network for Click-Through Rate Prediction.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

KEEP: An Industrial Pre-Training Framework for Online Recommendation via Knowledge Extraction and Plugging.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2020
CAN: Revisiting Feature Co-Action for Click-Through Rate Prediction.
CoRR, 2020

2019
Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling.
CoRR, 2019

Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction.
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Deep Interest Evolution Network for Click-Through Rate Prediction.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Rocket Launching: A Universal and Efficient Framework for Training Well-Performing Light Net.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Improved Compare-Aggregate Model for Chinese Document-Based Question Answering.
Proceedings of the Natural Language Processing and Chinese Computing, 2017

A Compare-Aggregate Model with Dynamic-Clip Attention for Answer Selection.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017


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