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Karen Uhlenbeck

How many mathematicians does it take to beat a snow storm?

As the weather reports came in with promise of blizzard and chaos, members of the Abel Prize Committee were determined to hold a final and conclusive meeting at the Institute of Advanced Study at Princeton. This is where they decide on the Abel Prize Laureate, and not even the whirling snow couldn't stop the following Abel Symposium. See the videos from the Abel Symposium here

Chair of the Abel Prize Committee, professor Helge Holden and the other committee-members finally came to a decision. However, they will keep this close to their chests untill the announcement March 19.

IAS have made the lectures available on their Youtube-channel. You can also view them in their entirety below.

Welcome remarks from David Nirenberg and Helge Holden

Welcome remarks from David Nirenberg and Helge Holden

Abstract

Karen Uhlenbeck, University of Texas, Austin, IAS:
"A Sampling of Minimization Problems"
Much of mathematics is connected with minimizing (or maximizing)
quantities. We will look at what the Greek’s were thinking, sample a
few problems from the early days of calculus, explain Hilbert’s 23
problem, mention my thesis work on Morse theory and Yau’s
contribution to geometric analysis and take a look at the geometry of the
Deep Linear Network model in AI. Time permitting I will return to one
of the problems I thought about as I graduate student which I still cannot
solve.

Karen Uhlenbeck - A Sampling of Minimization Problems

Daniel Spielman, Yale University:
"Discrepancy Theory is Mathematics, Computer Science, and Statistics"

Theorems in Discrepancy Theory tell us that it is possible to divide a set of vectors into two sets that look surprisingly similar to each other. In particular, these sets can be much more similar to each other than those produced by a random division.  The development of discrepancy theory has been motivated by applications in fields including combinatorics, geometry, optimization, and functional analysis.

Until a breakthrough of Bansal in 2010, the major algorithmic problems of discrepancy theory were thought to be computationally intractable. We now know efficient algorithms that solve many discrepancy problems, and the development of these algorithms has led to new proof techniques and new theorems.

We expect the greatest impact of discrepancy theory will be to the design of randomized controlled trials (RCTs), where it can be used to ensure similarity of test and control groups.

This talk will survey major mathematical and algorithmic results of discrepancy theory, along with recent advances, open problems, and applications.

Daniel Spielman - Discrepancy Theory is Mathematics Computer Science, and Statitics

Hong Wang, IHES and NYU:
"A survey of Stein's restriction conjecture"

Stein's Restriction conjecture concerns functions whose Fourier transform is supported on the unit sphere in R^n. Over the decades, progress on this problem has drawn on tools from combinatorics, real algebraic geometry, and other areas. We will survey the development of the conjecture and discuss its recent connections to projection theory.

Hong Wang - A survey of Stein's restriction conjecture

Curtis Mullen, Harvard University:
"Quintics, braids and billiards, After Abel”

Curtis Mullen - Quintics, braids and billiards, After Abel