AnyBoost.jl

A julia based machine learning package for boosting any loss, activation and constraint.
Author rakeshvar
Popularity
5 Stars
Updated Last
9 Months Ago
Started In
June 2019

AnyBoost.jl

A julia based machine learning package for boosting any loss, activation and constraint.

This package implements the first order methods discussed in my PhD thesis from the Department of Statistics at Stanford University under Prof. Trevor Hastie. The Thesis is titled “Boosting Like Path Algorithms for L1 Regularized Infinite Dimensional Convex Neural Networks”.

This package can be used to solve any Sparse Inverse Problem, once the required subroutines are implemented.