72 citations · 263 across the 31 of their papers we have counts for
4 papers · 1 filter
Accelerating Gradient Boosting Machine
Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva +1
Gradient Boosting Machine (GBM) is an extremely powerful supervised learning algorithm that is widely used in practice. GBM routinely features as a leading algorithm in machine lea…
Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems
Shuaiwen Wang, Wenda Zhou, Arian Maleki +2
Consider the following class of learning schemes: \begin{equation} \label{eq:main-problem1} \hat{\boldsymbolβ} := \underset{\boldsymbolβ \in \mathcal{C}}{\arg\min} \;\sum_{j=1}^n \…
Randomized Gradient Boosting Machine
Haihao Lu, Rahul Mazumder
Gradient Boosting Machine (GBM) introduced by Friedman is a powerful supervised learning algorithm that is very widely used in practice---it routinely features as a leading algorit…
Depth Creates No Bad Local Minima
Haihao Lu, Kenji Kawaguchi
In deep learning, \textit{depth}, as well as \textit{nonlinearity}, create non-convex loss surfaces. Then, does depth alone create bad local minima? In this paper, we prove that wi…