Fundamentals of Data Analysis

Dates: Tuesday July 24, 2018 to Saturday July 28, 2018
Venue: University of Wisconsin-Madison, Discovery Building, Orchard View Room
Sponsored by: NSF TRIPODS Institutes at the University of Wisconsin-Madison, the University of Washington, and the University of California-Berkeley.
Description: This summer school will introduce participants to a broad range of fundamental techniques used in modern data science and its applications. The emphasis will be on foundational concepts from statistics, computer science and mathematics with an eye towards fostering cross-disciplinary research within these fields. Topics will include: randomized linear algebra; high-dimensional statistics; interactive machine learning; probability on graphs; continuous optimization; deep learning.
Pre-requisites: The intended audience for the summer school are advanced graduate students and postdoctoral researchers with a background in statistics, computer science, mathematics or related fields.
Organizing Committee: Maryam Fazel, Po-Ling Loh, Sebastien Roch, Steve Wright

Applications for the summer school are currently under review. Preference will be given to attendees affiliated with TRIPODS institutes, and to PhD students and postdoctoral researchers. No travel support is available; attendees (or their sponsors) are responsible for their own costs. 

● Topic I: Randomized Linear Algebra (Michael Mahoney, UC-Berkeley) 3 lectures, 1 lab
● Topic II: High-dimensional Statistics (Po-Ling Loh, UW-Madison) 2 lectures, no lab
● Topic III: Interactive ML (Rob Nowak, UW-Madison) 2 lectures
● Topic IV: Graphs and Networks (Sebastien Roch, UW-Madison) 2 lectures, 1 lab
● Topic V: Continuous Optimization (Stephen Wright, UW-Madison; Maryam Fazel, U. Washington; Dmitriy Drusvyatskiy, U. Washington) 3 lectures, 1 lab
● Topic VI: Deep Learning (Zaid Harchaoui, U. Washington) 1 lecture+2 labs.

Tuesday July 24

9:00-10:30 Lecture I: Rand Lin Alg
10:30-11:00 Break
11:00-12:30 Lecture I: Rand Lin Alg
12:30-2:00 Lunch
2:00-3:30 Lecture II: High-Dim Stats
3:30-4:00 Break
4:00-5:15 Problem Session / Lab I: Rand Lin Alg
5:15-6:30 Poster Session / Reception WID Optimization Area

Wednesday July 25

9:00-10:30 Lecture I: Rand Lin Alg
10:30-11:00 Break
11:00-12:30 Lecture Lecture II: High-Dim Stats
12:30-2:00 Lunch
2:00-3:30 Lecture III: Interactive ML
3:30-4:00 Break
4:00-5:15 Lecture III: Interactive ML

Thursday July 26

9:00-10:30 Lecture IV: Graphs and Nets
10:30-11:00 Break
11:00-12:30 Lecture IV: Graphs and Nets
12:30-2:00 Lunch
2:00-3:30 Lecture V: Continuous Opt
3:30-4:00 Break
4:00-5:15 Problem Session / Lab IV: Graphs and Nets

Friday July 27

9:00-10:30 Lecture V: Continuous Opt
10:30-11:00 Break
11:00-12:30 Lecture V: Continuous Opt
12:30-2:00 Lunch
2:00-3:30 Lecture VI: Deep Learning
3:30-4:00 Break
4:00-5:15 Problem Session / Lab V: Continuous Opt
6:30-9:00 Games Night (Board Games, Junk Food, and Fun) WID Optimization Area

Saturday July 28

9:00-10:30 Lecture/Lab VI: Deep Learning
10:30-11:00 Break
11:00-12:30 Lab VI: Deep Learning
12:30-12:45 Closing