Lecturer in Statistical Science,
School of Mathematics,
University of Bristol.
Turing Fellow, Alan Turing Institute.
Office GA.18
Fry Building,
Woodland Road, BS8 1UG.
*The actual person may look slightly bigger different than the image. 🙃
I am a statistical machine learning researcher who has been mostly working on Density Ratio Estimation. I have a vision that by comparing two density functions, many machine learning problems can be solved more elegantly and efficiently. We have seen many important works being done along this line, such as Generative Adversarial Net.
(AAAI 2021) Minami, S., Liu, S., Wu, S., Fukumizu, K., Yoshida, R., A General Class of Transfer Learning Regression without Implementation Cost, AAAI Conference on Artificial Intelligence, To appear, 2021.
(NEURIPS2019) Liu, S., Kanamori, T., Jitkrittum, W., Chen, Y. Fisher Efficient Inference of Intractable Models,_ Advances in Neural Information Processing Systems 32_, 2019.
(ICML2019) Wu, X. Z., Liu, S., Zhou, Z.H. Heterogeneous Model Reuse via Optimizing Multiparty Multiclass Margin, Proceedings of the 36th International Conference on Machine Learning, PMLR 97, 2019.
(NC2018) Noh, Y-K., Sugiyama, M., Liu, S., du Plessis, M.C., Park, F.C., and Lee, D. D., Bias Reduction and Metric Learning for Nearest−Neighbor Estimation of Kullback−Leibler Divergence, Neural Computation Vol.30(7), 2018
(NEURIPS2017) Liu, S., Takeda, A., Suzuki, T., Fukumizu K., Trimmed Density Ratio Estimation, Advances in Neural Information Processing Systems 30, 2017
(AOS2017) Liu, S., Suzuki, T., Relator R., Sese J., Sugiyama, M., Fukumizu, K., Support consistency of direct sparse-change learning in Markov networks. Annals of Statistics, Volume 45, Number 3, 2017
(ICML2016) Liu, S., Suzuki, T., Sugiyama, M. Fukumizu K., Structure Learning of Partitioned Markov Networks, Proceedings of the 33rd International Conference on Machine Learning, 2016.
(SDM 2016) Liu, S., Fukumizu K., Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective, Proceedings of 2016 SIAM International Conference on Data Mining, 2016.
03/2014, Doctor of Engineering, Tokyo Institute of Technology, Japan.
Thesis: Statistical Machine Learning Approaches on Change Detection.
Supervisor: Prof. Masashi Sugiyama
10/2010, Master of Science with Distinction, University of Bristol, UK.
06/2009, Bachelor of Engineering, Soochow University, China.