Organizing Committee


Invited Speakers

Program and Venue




The First International Conference on
Mathematics of Data Science (MathDS)

20-24 March 2017



Program: (Book of Abstracts)

20 Mar 2017 (Mon)
SWT501, Shaw Tower, Shaw Campus
Morning Session Chair: Michael Ng
09:20-09:30 Opening
09:30-10:10 Charles Chui
Means for knowledge dissemination with samples and case studies
10:10-10:50 Gerlind Plonka
Sparse phase retrieval of one-dimensional signals by Prony's method
10:50-11:10 Break
11:10-11:50 Sergei Pereverzyev
Balancing principle in supervised learning for a general regularization scheme
11:50-12:30 Dao-Qing Dai
Sparse dictionary regression with applications
12:30-14:00 Lunch (by invitation)
Afternoon Session Chair: Charles Chui
14:00-14:40 Matthew Hirn
Learning many body physics via multiscale, multilayer machine learning architectures
14:40-15:20 Jianzhong Wang
Ensemble boosting algorithms based on data sorting for semi-supervised classification
15:20-16:00 Break
16:00-16:40 Tao Qian
Adaptive orthonormal systems for matrix-valued functions
16:40-17:20 M.D. van der Walt
Atomic signal decomposition via SuperEMD
17:20-18:00 Haizhao Yang
Recursive schemes for shape functions in the mode decomposition problem
21 Mar 2017 (Tue)
SWT501, Shaw Tower, Shaw Campus
Morning Session Chair: Ding-Xuan Zhou
09:30-10:10 Frèdèric Chazal
Data driven estimation of the Laplace-Beltrami operator
10:10-10:50 Raymond H. Chan
Geometric tight frame based stylometry for an Authentication of van Gogh paintings
10:50-11:10 Break
11:10-11:50 Zhiqiang Xu
The minimal measurement number for low-rank matrix recovery
11:50-12:30 Jianfeng Cai
Non-convex methods for low-rank matrix reconstruction
12:30-14:00 Lunch (by invitation)
Afternoon Session Chair: Henry Ngan
14:00-14:40 Wenchang Sun
Frames of uniform subframe bounds with applications to erasures
14:40-15:20 Shaobo Lin
Distributed semi-supervised learning
15:20-16:00 Break
16:00-16:40 Ting Hu
Convergence of gradient descent for kernel minimum error entropy principle
16:40-17:20 Junhui Wang
Gradient-induced model-free variable selection
17:20-18:00 Can Yang
Adaptive False Discovery Rate regression with application in integrative analysis of large-scale genomic data
22 Mar 2017 (Wed)
SWT501, Shaw Tower, Shaw Campus
Morning Session Chair: Charles Chui
09:30-10:10 Yuesheng Xu
Mathematics in data science
10:10-10:50 Sergiy Pereverzyev Jr.
Adaptive Nyström subsampling for dealing with Big Data
10:50-11:10 Break
11:10-11:50 Lihua Yang
Questions on mono-components
11:50-12:30 Xin Guo
Convergence of the Randomized Kaczmarz Algorithm in Hilbert Space
12:30-14:00 Lunch (by invitation)
Afternoon Session Chair: Michael Ng
14:00-14:40 Xiaoming Huo
Challenges in data science and a possible roadmap of future work
14:40-15:20 Qiang Wu
Bias correction for regularized kernel regression with applications in distributed learning
15:20-16:00 Break
16:00-16:40 Weiguo Gao
Algorithms for group sparsity with overlap and beyond
16:40-17:20 Wai-Ki Ching
Construction of probabilistic boolean networks with applications
17:20-18:00 Xiaosheng Zhuang
Multiscale data analysis: Framelets, manifolds and graphs
18:30 Banquet (by invitation)
23 Mar 2017 (Thu)
FSC501, Fong Shu Chuen Library, Ho Sin Hang Campus
Morning Session Chair: Henry Ngan
09:30-10:10 Simon Foucart
Computing a quantity of interest from observational data
10:10-10:50 Lek-Heng Lim
Tensor network ranks
10:50-11:10 Break
11:10-11:50 Jian Huang
A constructive approach to L0-penalized linear regression
11:50-12:30 Hongzhi Tong
Calibration of $\varepsilon$-insensitive loss in support vector machines regression
12:30-14:00 Lunch (by invitation)
24 Mar 2017 (Fri)
SWT501, Shaw Tower, Shaw Campus
Morning Session Chair: Henry Ngan
09:30-10:10 Holger Wendland
Kernel-based reconstructions for parametric PDEs
10:10-10:50 Ronald Lok Ming Lui
Restoration of atmospheric turbulence-distorted images via RPCA and Quasiconformal maps
10:50-11:10 Break
11:10-11:50 Sou-Cheng Terrya Choi
Probabilistic record linkage and address standardization
11:50-12:30 Xiaojun Chen
Nonsmooth, nonconvex regularization for sparse optimization
12:30-14:00 Lunch (by invitation)
Afternoon Session Chair: Ding-Xuan Zhou
14:00-14:40 Xiaoming Yuan
How to implement ADMM to large-scale datasets?
14:40-15:20 Yingchun Jiang
Spatially distributed sampling and reconstruction of signals on a graph
15:20-16:00 Yuan Yao
Boosting with structural sparsity – A differential inclusion approach








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