Geometric Understanding of Data in 3D and Higher - Part II of III
For Part I, see MS-Th-E-05
For Part III, see MS-Fr-E-05

Date: August 14
Time: 13:30--15:30
Room: 215

(Note: Click title to show the abstract.)

Lai, Rongjie (Rensselaer Polytechnic Inst.)
Zhao, Hongkai (UC Irvine)

Abstract: Rapid development of data acquisition technology stimulates research on developing new computational tools for analyzing and processing data to make more effective decisions. In many problems, coherent structures of data allows us to model data as a low dimension manifold in a high dimension space. More recently, there has been increasing interests in using geometric based method to analyze and infer underlying structures from the given data. This minisymposium aims to bring together people from different research groups with common interest. We hope that this symposium can propel further collaborations and developments in this field.

A Novel Geometric Multiscale Approach to Structured Dictionary Learning on High Dimensional Data
Chen, Guangliang (San Jose State Univ.)

Understanding data from incomplete distance information via solutions of Geometric PDEs.
Lai, Rongjie (Rensselaer Polytechnic Inst.)

Data analysis tools for large-scale computer vision and multi-media information retrieval
Bronstein, Alexander (Tel Aviv Univ.)

Fast Multiscale Optimal Transport for point clouds in high dimensions
Maggioni, Mauro (Duke Univ.)


Code: Type-Date-Time-Room No.
Type : IL=Invited Lecture, SL=Special Lectures, MS=Minisymposia, IM=Industrial Minisymposia, CP=Contributed Papers, PP=Posters
Date: Mo=Monday, Tu=Tuesday, We=Wednesday, Th=Thursday, Fr=Friday
Time : A=8:30-9:30, B=10:00-11:00, C=11:10-12:10, BC=10:00-12:10, D=13:30-15:30, E=16:00-18:00, F=19:00-20:00, G=12:10-13:30, H=15:30-16:00
Room No.: TBA