no code implementations • 6 Feb 2023 • Nahuel Statuto, Irene Unceta, Jordi Nin, Oriol Pujol
Differential replication through copying refers to the process of replicating the decision behavior of a machine learning model using another model that possesses enhanced features and attributes.
2 code implementations • 27 May 2021 • Carlos Mougan, David Masip, Jordi Nin, Oriol Pujol
Regression problems have been widely studied in machinelearning literature resulting in a plethora of regression models and performance measures.
no code implementations • 15 Jul 2020 • Irene Unceta, Jordi Nin, Oriol Pujol
When deployed in the wild, machine learning models are usually confronted with data and requirements that constantly vary, either because of changes in the generating distribution or because external constraints change the environment where the model operates.
no code implementations • 1 Oct 2019 • Irene Unceta, Diego Palacios, Jordi Nin, Oriol Pujol
Copies have been proposed as a viable alternative to endow machine learning models with properties and features that adapt them to changing needs.
no code implementations • 5 Mar 2019 • Irene Unceta, Jordi Nin, Oriol Pujol
We study model-agnostic copies of machine learning classifiers.
no code implementations • 19 Nov 2018 • Irene Unceta, Jordi Nin, Oriol Pujol
We use a private residential mortgage default dataset as a use case to illustrate the feasibility of this approach to ensure the decomposability of attributes during pre-processing.