15 citations · 17 across the 2 of their papers we have counts for
4 papers
Anytime Optimal Decision Tree Learning with Continuous Features
Harold Kiossou, Pierre Schaus, Siegfried Nijssen
In recent years, significant progress has been made on algorithms for learning optimal decision trees, primarily in the context of binary features. Extending these methods to conti…
A Generic Complete Anytime Beam Search for Optimal Decision Tree
Harold Silvère Kiossou, Siegfried Nijssen, Pierre Schaus
Finding an optimal decision tree that minimizes classification error is known to be NP-hard. While exact algorithms based on MILP, CP, SAT, or dynamic programming guarantee optimal…
An LSTM approach to Forecast Migration using Google Trends
Nicolas Golenvaux, Pablo Gonzalez Alvarez, Harold Silvère Kiossou +1
Being able to model and forecast international migration as precisely as possible is crucial for policymaking. Recently Google Trends data in addition to other economic and demogra…
Using an interpretable Machine Learning approach to study the drivers of International Migration
Harold Silvère Kiossou, Yannik Schenk, Frédéric Docquier +3
Globally increasing migration pressures call for new modelling approaches in order to design effective policies. It is important to have not only efficient models to predict migrat…