2 papers
math.OC2018
Exploiting Low-Rank Structure in Semidefinite Programming by Approximate Operator Splitting
Mario Souto, Joaquim D. Garcia, Alvaro Veiga
In contrast with many other convex optimization classes, state-of-the-art semidefinite programming solvers are yet unable to efficiently solve large scale instances. This work aims…
stat.ML2018
BooST: Boosting Smooth Trees for Partial Effect Estimation in Nonlinear Regressions
Yuri Fonseca, Marcelo Medeiros, Gabriel Vasconcelos +1
In this paper, we introduce a new machine learning (ML) model for nonlinear regression called the Boosted Smooth Transition Regression Trees (BooST), which is a combination of boos…