Regularization vs. Relaxation: A conic optimization perspective of statistical variable selection

no code implementations • 20 Oct 2015 • Hongbo Dong, Kun Chen, Jeff Linderoth

In particular, we show that a popular sparsity-inducing concave penalty function known as the Minimax Concave Penalty (MCP), and the reverse Huber penalty derived in a recent work by Pilanci, Wainwright and Ghaoui, can both be derived as special cases of a lifted convex relaxation called the perspective relaxation.

Combinatorial Optimization Variable Selection