优化、稀疏性与自适应数据分析国际会议

In recent years, there has been an explosive growth in developing new efficient algorithms to represent large scale data or multiscale solutions. The L1-based optimization, sparsity, and low rank structures have played in an important role in the recent developments of compressed (compressive) sensing and various fast algorithms for image processing, data analysis and high frequency wave propagation. Many problems in multiscale solutions and stochastic PDEs with high dimensional input variables enjoy low rank structure when the solution is projected to some appropriately chosen data-driven basis. At the same time, there is a lot of progress in developing adaptive data analysis methods for analyzing nonlinear nonstationary data. These methods can reveal some intrinsic physical features from multiscale data. Statistical analysis has also played a significant role in modern data analysis. This workshop will bring experts from these different disciplines together to exchange ideas and identify new research opportunities at the interface between information science and physical sciences.