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The alignment principle

Kellie MacPhee, University of Washington
Wednesday, January 30, 2019 - 3:30pm to 4:30pm
THO 202

The notion of "alignment" between points in a primal space and points in a dual space can be used to characterize optimality conditions for many common optimization problems. This gives a nice geometric interpretation of what it means for points to be optimal, in settings including 1) regularization in machine learning, 2) gauge duality, and 3) linear conic optimization. I will give an overview of what the alignment principle is, relate it to a generalized notion of sparsity, and discuss its application in the three settings above.

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