2013-14: LDHD: LDHD Summer School: August 11-16, 2013

Location

This summer school was held at the Radisson Hotel in Research Triangle Park, NC.

Description

Recent technological advancements allow for the collection of higher dimensional data as well as data with more complicated structure. A fundamental problem is to identify low- dimensional structure in high-dimensional systems (LDHD). The challenges in addressing these problems are theoretical as well as computational and intersect with many application areas. This summer school gave students an overview of the fast growing area of LDHD, as a prelude to the year-long SAMSI program on LDHD.

The school covered existing theoretical and computational tools to analyze LDHD. The short courses were at the graduate level; they were aimed at advanced PhD students, postdocs, and faculty.

The titles, lecturers, and prerequisites for the courses:

  1. Title: Topological and geometrical structures in data analysis
    Lecturer: Vin de Silva
    Prereqs: basic knowledge of analysis is assumed; some knowledge of topology is useful but not required
  2. Title: Bayesian learning from big data
    Lecturer: David Dunson
    Prereqs: basic familiarity with the Bayesian paradigm (course is aimed at advanced graduate students, postdoctoral fellows, and faculty with expertise in statistics); recommended background reading: the initial chapters in “A First Course in Bayesian Statistical Methods”, by Peter Hoff
  3. Title: Population and familial structure in genetic association studies
    Lecturer: Ann Lee
    Prereqs: none specified
  4. Title: Randomness in geometry and topology: finding order in the chaos
    Lecturer: Elizabeth Meckes
    Topics: topology of randomly constructed spaces; low-dimensional projections of high-dimensional distributions; random unitary matrices; probability and high- dimensional convex geometry
    Prereqs: undergrad-level probability theory and matrix analysis
  5. Title: Convex and nonconvex methods for high dimensional sparse estimation
    Lecturer: Tong Zhang
    Prereqs: prior exposure to sparsity and high dimensional statistics
  6. Title: Genomics and high-dimensional optimization
    Lecturer: Hua Zhou
    Prereqs: interest in modern genomics, computation, or both

Questions: email [email protected]

Schedule and Supporting Media

Sunday, August 11, 2013
Radisson RTP

Time Description Speaker Slides Videos
9:00-9:30 Registration and Continental Breakfast
9:30-9:40 Welcome
9:40-10:40 Topological and Geometrical Structures in Data Analysis Vin de Silva, Pomona College  
11:05-12:30 Randomness in Geometry and Topology: Finding Order in the Chaos Elizabeth Meckes, Case Western University    
12:30-2:00 Lunch (Galeria Restaurant, first floor)
2:00-3:15 Population and Familial Structure in Genetic Association Studies Ann Lee, Carnegie Mellon University    
3:45-5:00 Random Unitary Matrices and Friends Elizabeth Meckes, Case Western University    

Monday, August 12, 2013
Radisson RTP

Time Description Speaker Slides Videos
9:00-9:30 Continental Breakfast
9:30-10:45 Population and Familial Structure in Genetic Association Studies:Part 2 Ann Lee, Carnegie Mellon University    
11:00-12:15 Elizabeth Meckes, Case Western University
12:15-2:00 Lunch (Room ABC, second floor)
2:00-3:00 Topological and Geometrical Structures in Data Analysis Vin de Silva, Pomona College  
3:30-4:45 Elizabeth Meckes, Case Western University
5:00-6:30 Poster Session and Reception

Tuesday, August 13, 2013
Radisson RTP

Time Description Speaker Slides Videos
9:00-9:30 Continental Breakfast
9:30-11:00 Bayesian Learning from Big Data David Dunson, Duke University    
11:30-12:30 Topological & Geometrical Structures in Data Analysis – Lecture 3 Vin de Silva, Pomona College    
12:30-1:30 Box Lunches/Adjourn for the Day

Wednesday, August 14, 2013
Radisson RTP

Time Description Speaker Slides Videos
9:00-9:30 Continental Breakfast
9:30-11:00 Sparse Bayesian factor models David Dunson, Duke University    
11:30-12:30 Topological and Geometrical Structures in Data Analysis – Lecture 4 Vin de Silva, Pomona College    
12:30-2:00 Lunch (Rooms ABC, second floor)
2:00-3:00 Topological and Geometrical Structures in Data Analysis – Lecture 5 Vin de Silva, Pomona College  
3:30-5:00 Baysian factorizations of huge tensors David Dunson, Duke University  

Thursday, August 15, 2013
Radisson RTP

Time Description Speaker Slides Videos
9:00-9:30 Continental Breakfast
9:30-10:45 Genomics and High-Dimensional Optimization Hua Zhou, North Carolina State University    
11:15-12:30 Discussion
12:30-2:00 Lunch (Rooms ABC, second floor)
2:00-3:15 Sparse Regression (from low dimension to high dimension) Tong Zhang, Rutgers University    
3:45-5:00 Convex Relaxation Structured Sparsity and Matrix Regularization Tong Zhang, Rutgers University  

Friday, August 16, 2013
Radisson RTP

Time Description Speaker Slides Videos
9:00-9:30 Continental Breakfast
9:30-10:45 Convex Optimization Tong Zhang, Rutgers University  
11:15-12:30 Hua Zhou, North Carolina State University  
12:30-2:00 Lunch (Rooms ABC, second floor)
2:00-3:15 Sparse Regression with Non-Convex Regularization Tong Zhang, Rutgers University  
3:45-5:00 Discussion
5:00 Adjourn