The Boot Camp is intended to acquaint program participants with the key themes of the program. It will consist of five days of tutorial presentations as follows:

Ravi Kannan (Microsoft Research India) - Foundations of Data Science
David Woodruff (CMU) - Sketching for Linear Algebra: Basics of Dimensionality Reduction and CountSketch
Ken Clarkson (IBM Almaden) - Sketching for Linear Algebra III: Randomized Hadamard, Kernel Methods
Rachel Ward (UT Austin) - First-Order Stochastic Optimization
Michael Mahoney (ICSI & UC Berkeley) - Sampling for Linear Algebra and Optimization
Fred Roosta (University of Queensland) - Stochastic Second Order Optimization Methods
Will Fithian (UC Berkeley) - Statistical Interference
Santosh Vempala (Georgia Tech) - High Dimensional Geometry and Concentration
Ilias Diakonikolas (USC) - Algorithmic High Dimensional Robust Statistics
Ilya Razenshteyn (Microsoft Research) - Nearest Neighbor Methods
Michael Kapralov (EPFL) - Data Streams