Yawen Liu

ORCID: 0009-0005-3047-9619
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About
Contact & Profiles
Research Areas
  • Recommender Systems and Techniques
  • Mobile Crowdsensing and Crowdsourcing
  • Higher Education and Teaching Methods
  • Radiomics and Machine Learning in Medical Imaging
  • Advanced Bandit Algorithms Research
  • Web Data Mining and Analysis
  • Bayesian Modeling and Causal Inference
  • Data Stream Mining Techniques
  • Customer churn and segmentation
  • Second Language Learning and Teaching
  • Optimization and Search Problems
  • Advanced Decision-Making Techniques
  • Expert finding and Q&A systems
  • Military Defense Systems Analysis
  • Global Education and Multiculturalism
  • Medical Imaging Techniques and Applications
  • Data Mining Algorithms and Applications
  • Advanced MRI Techniques and Applications

Merck (Singapore)
2024

Quzhou University
2016

Most existing LTR approaches follow a supervised learning paradigm from offline data collected the online system. However, it has been noticed that previous models can have good performances over validation but poor performances, which implies possible large inconsistency between and evaluation. We investigate confirm in this paper such exists significant impact on AliExpress Search. Reasons for include ignorance of item context. Therefore, proposes an evaluator-generator framework with The...

10.1109/tkde.2021.3098898 article EN IEEE Transactions on Knowledge and Data Engineering 2021-01-01

10.1145/3626772.3657870 article EN Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval 2024-07-10

Rapid quantitative magnetic resonance imaging (qMRI) is the trend of MR development and has essential diagnostic value. However, reducing acquisition time will come at expense image quality also affect accuracy values. Here we propose a method for reconstructing fast low-resolution qMRI images using deep learning, aiming to improve while bias in The research results show that after comparable conventional high-resolution scanning images, values are more stable.

10.58530/2023/1618 article EN Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition 2024-08-14

Learning-to-rank (LTR) has become a key technology in E-commerce applications. Most existing LTR approaches follow supervised learning paradigm from offline labeled data collected the online system. However, it been noticed that previous models can have good validation performance over but poor performance, and vice versa, which implies possible large inconsistency between evaluation. We investigate confirm this paper such exists significant impact on AliExpress Search. Reasons for include...

10.48550/arxiv.2003.11941 preprint EN other-oa arXiv (Cornell University) 2020-01-01

English teaching ability development is an important part of pedagogical education and reform, the basis for helping students to reach a high attainment level improve learning living quality, basic guarantee success reform.The deepening course reform brings about severe challenges in ability.The specialized teacher makes more demanding profession.This paper discussed effective patterns improving majors, offered suggestions on mode skill training majors.

10.2991/ssehr-16.2016.109 article EN cc-by-nc 2016-01-01

This study explores the importance and strategies of teaching cross-cultural understanding in English at vocational schools from perspective core competencies. Integrating concept competencies into education fosters students' overall quality provides a foundation for understanding. The research emphasizes needs, examines relationship between competence, assesses its impact on courses schools. Teaching encompass goal setting, material selection, classroom methods, assessment, teacher...

10.25236/fer.2023.062818 article EN Frontiers in Educational Research 2023-01-01

Recent E-commerce applications benefit from the growth of deep learning techniques. However, we notice that many works attempt to maximize business objectives by closely matching offline labels which follow supervised paradigm. This results in models obtain high performance terms Area Under Curve (AUC) and Normalized Discounted Cumulative Gain (NDCG), but cannot consistently increase revenue metrics such as purchases amount users. Towards issues, build a simulated search engine AESim can...

10.48550/arxiv.2107.07693 preprint EN other-oa arXiv (Cornell University) 2021-01-01

In the process of ASW patrol aircraft cooperative search target, there is a lot uncertainty in situation evaluation problem. order to deal with uncertain information, cloud theory and Bayesian network are introduced, method based on proposed deduce enemy's operational intention form battlefield situation. Firstly, model target established. Secondly, used for discretization. After determining conditional probability table(CPT) each node conversion between certainty probability, final grade...

10.1109/ihmsc52134.2021.00049 article EN 2021-08-01
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