Impact of weather factors on migration intention using machine learning algorithms

no code implementations • 4 Dec 2020 • John Aoga, Juhee Bae, Stefanija Veljanoska, Siegfried Nijssen, Pierre Schaus

A growing attention in the empirical literature has been paid to the incidence of climate shocks and change in migration decisions.

BIG-bench Machine Learning

Using an interpretable Machine Learning approach to study the drivers of International Migration

no code implementations • 5 Jun 2020 • Harold Silvère Kiossou, Yannik Schenk, Frédéric Docquier, Vinasetan Ratheil Houndji, Siegfried Nijssen, Pierre Schaus

a traditional model, and 2) using PDP we are able to gain additional insights on the specific effects of the migration drivers.

BIG-bench Machine Learning Feature Importance +1

Stochastic Constraint Optimization using Propagation on Ordered Binary Decision Diagrams

no code implementations • 3 Jul 2018 • Anna L. D. Latour, Behrouz Babaki, Siegfried Nijssen

For the specific case of monotonic distributions, we suggest an alternative method for using CP in SCOP, based on the development of a new propagator; we show that this propagator is linear in the size of the OBDD, and has the potential to be more efficient than the decomposition method, as it maintains domain consistency.

The Inductive Constraint Programming Loop

no code implementations • 12 Oct 2015 • Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis

Constraint programming is used for a variety of real-world optimisation problems, such as planning, scheduling and resource allocation problems.

BIG-bench Machine Learning Scheduling