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<span style="font-size:xx-large;">陆恒杨 Heng-Yang Lu</span> | <span style="font-size:xx-large;">陆恒杨 Heng-Yang Lu</span> | ||
| − | <span style="font-size:larger;">PhD Candidate @ IIP Group<br/> Department of Computer Science<br/> National Key Laboratory for Novel Software Technology<br/> Nanjing University</span> | + | <span style="font-size:larger;">PhD Candidate @ IIP Group<br/> Department of Computer Science and Technology<br/> National Key Laboratory for Novel Software Technology<br/> Nanjing University</span> |
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2017年6月30日 (五) 21:53的版本
Heng-Yang Lu @ NJUCS, hylu@smail.nju.edu.cn
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陆恒杨 Heng-Yang Lu PhD Candidate @ IIP Group |
Supervisor
Professor Jun-Yuan Xie and Professor Chong-Jun Wang
Biography
I received my B.Sc. degree in Department of Computer Science and Technology of Nanjing University in June 2014. In the same year, I was admitted to study for a Phd degree in Nanjing University without entrance examination.
Currently I am a first year PhD student of Department of Computer Science and Technology in Nanjing University and a member of IIP Group, led by professor Jun-Yuan Xie and Chong-Jun Wang.
Research Interest
I am interested in Machine Learning and Natural Language Process. Currently I am focusing on the subfields:
- machine learning applications
- topic modoel in short text scenario
News
- Apr.26-28, 2017: Invited talk at 12th Annual Symposium on Future Trends in SOC, Potsdam, Germany
- Feb.02-09, 2017: Poster night at 31th AAAI Conference, San Francisco, USA
- Nov.07-08, 2016: Presentation and elevator pitch at 5th HPI Research School at NJU Workshop, Nanjing, China
- Nov.09-11, 2015: Oral talk at 27th ICTAI Conference, Vietri sul Mare, Italy
Publications
- Lu H, Xie L, Kang N, Wang C and Xie J. Don't Forget the Quantifiable Relationship between Words: Using Recurrent Neural Network for Short Text Topic Discovery[C]. In Proceedings of AAAI-17. San Francisco, USA, 2017: 1192-1198.
- Jiang L, Lu H, Xu M and Wang C. Biterm Pseudo Document Topic Model for Short Text[C]. In Proceedings of ICTAI-16. San Jose, USA, 2016: 865-872.
- Lu H, Li N and Xie J. A Region of Interest Detection Method for Mammography based on Multi-cue Feature Integration[J]. Journal of Nanjing University: Nat Sci Ed, 2016, 52(1): 194-202.
- Lu H, Chen F, Xu M, Wang C and Xie J. Never Ignore The Significance Of Different Anomalies: A Cost-sensitive Algorithm Based On Loss Function For Anomaly Detection[C]. In Proceedings of ICTAI-15. Vietri sul Mare, Italy, 2015: 1099-1105.
