Research Output per year
Personal profile
Biography
Dr Lan Du is a Teaching and Research Academic in the Faculty of IT, Monash Clayton Campus. He is particularly interested in statistical modeling and learning for text analysis, which broadly covers statistical machine learning, natural language processing, data mining, and social network analysis. My up-to-date information can be found here
Some specific research topics that he is interested in and currently working on:
- Probabilistic topic modeling: He is extremely interested in developing various topic models that can explore different discourse structures and other meta information associated with natural language text.
- Nonparametric Bayesian methods, e.g., Dirichlet process, Pitman-Yor process, and Indian Buffet process. He has been working on developing different sampling methods for Pitman-Yor process since his Ph.D. study.
- Inference/ optimization algorithms, e.g., MCMC methods, Variational Bayesian (VB), and various numerical optimization algorithms
- Relational learning techniques, e.g., probabilistic matrix factorization, tensor factorization, etc. He is interested in combining matrix factorization techniques with topic models to improve, for example, recommendation systems.
- Natural Language Processing. He has worked in the NLP group at Macquarie University for about four years. He is interested in how to utilize different linguistic features in topic modeling.
Monash teaching commitment
Dr Lan Du has experience as the Chief Examiner for the following units in the Faculty of IT:
- FIT5149 Applied data analysis
- FIT5196 Data wrangling
Lan Du has experience as the Lecturer for the following units in the Faculty of IT:
- FIT5149 Applied data analysis
- FIT5196 Data wrangling
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2008 2018
Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences
Zhao, H., Rai, P., Du, L. & Buntine, W. 2018 2018 Twenty-First International Conference on Artificial Intelligence and Statistics, AISTATS 2018 : 9-11 April 2018, Lanzarote, Canary Islands, Proceedings . Storkey, A. & Perez-Cruz, F. (eds.). Lanzarote, Canary Islands: PMLR, Vol. 84, p. 1943-1951 9 p. (Proceedings of Machine Learning Research; vol. 84)Research output: Chapter in Book/Report/Conference proceeding › Conference Paper
Leveraging external information in topic modelling
Zhao, H., Du, L., Buntine, W. & Liu, G. 12 May 2018 (Accepted/In press) In : Knowledge and Information Systems. p. 1-33 33 p.Research output: Contribution to journal › Article
Two-phase linear reconstruction measure-based classification for face recognition
Gou, J., Xu, Y., Zhang, D., Mao, Q., Du, L. & Zhan, Y. 1 Apr 2018 In : Information Sciences. 433-434, p. 17-36 20 p.Research output: Contribution to journal › Article
A Word Embeddings Informed Focused Topic Model
Zhao, H., Du, L. & Buntine, W. 2017 2017 Ninth Asian Conference on Machine Learning, ACML 2017: 15-17 November 2017, Seoul, Korea, Proceedings. Zhang, M-L. & Noh, Y-K. (eds.). PMLR, Vol. 77, p. 423-438 16 p. (Proceedings of Machine Learning Research; vol. 77)Research output: Chapter in Book/Report/Conference proceeding › Conference Paper
Leveraging Node Attributes for Incomplete Relational Data
Zhao, H., Du, L. & Buntine, W. 2017 34th International Conference on Machine Learning, ICML 2017: 6-11 August 2017, Sydney, Australia, Proceedings . Precup, D. & Teh, Y. W. (eds.). Proceedings of Machine Learning Research, Vol. 70, p. 4072-4081 10 p. (Proceedings of Machine Learning Research; vol. 70)Research output: Chapter in Book/Report/Conference proceeding › Conference Paper