Verifying Robustness of Gradient Boosted Models

no code implementations • 26 Jun 2019 • Gil Einziger, Maayan Goldstein, Yaniv Sa'ar, Itai Segall

Robustness to small perturbations of the input is an important quality measure for machine learning models, but the literature lacks a method to prove the robustness of gradient boosted models.

BIG-bench Machine Learning

Learning Software Constraints via Installation Attempts

no code implementations • 24 Apr 2018 • Ran Ben Basat, Maayan Goldstein, Itai Segall

Modern software systems are expected to be secure and contain all the latest features, even when new versions of software are released multiple times an hour.

Using Machine Learning to Detect Noisy Neighbors in 5G Networks

no code implementations • 24 Oct 2016 • Udi Margolin, Alberto Mozo, Bruno Ordozgoiti, Danny Raz, Elisha Rosensweig, Itai Segall

5G networks are expected to be more dynamic and chaotic in their structure than current networks.

BIG-bench Machine Learning Management