Boris Defourny

I work as a PhD student in the Systems and Modeling Research Unit, University of Liège, under the supervision of Louis Wehenkel.
I study approaches that mix models and techniques from Operations Research (Stochastic Programming) and Machine Learning (Supervised Learning, Reinforcement Learning). Relevant tools include convex optimization, combinatorial optimization, measure and probability theory, kernel methods, and Monte Carlo simulation. Applications are in sequential decision making under uncertainty and risk-aware decision making.

Contact Information

Address:
Systems and Modeling Research Unit,
University of Liège,
Montefiore (B28),
Grande Traverse, 10
Sart-Tilman
B-4000 Liège,
Belgium.

Phone: +32 4 366 2972
Email: bdf at montefiore dot ulg dot ac dot be

Publications

• Large Margin Classification with the Progressive Hedging Algorithm.
  B. Defourny and L. Wehenkel.
  OPT 2009: Second NIPS Workshop on Optimization for Machine Learning, Whistler, Canada, 2009.
• Bounds for Multistage Stochastic Programs using Supervised Learning Strategies.
  B. Defourny, D. Ernst and L. Wehenkel.
  Stochastic Algorithms: Foundations and Applications. Fifth International Symposium, SAGA 2009. Lecture Notes in Computer Science, vol. 5792, pp. 61-73, Springer, 2009.
  Postprint by Springer. Preprint.
  
• Supervised Learning of Intra-Daily Recourse Strategies for Generation Management Under Uncertainties.
  B. Cornelusse, G. Vignal, B. Defourny and L. Wehenkel.
  2009 IEEE Bucharest PowerTech.
• Probability Density Estimation by Perturbing and Combining Tree Structured Markov Networks.
  S. Ammar, P. Leray, B. Defourny and L. Wehenkel.
  Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 10th ECSQARU, Lecture Notes in Artificial Intelligence, vol. 5590, pp. 156-167, Springer, 2009.
• Planning under Uncertainty, Ensembles of Disturbance Trees and Kernelized Discrete Action Spaces.
  B. Defourny, D. Ernst and L. Wehenkel.
  Proceedings of the IEEE International Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL 2009), pp. 145-152, Nashville TN, 2009.
• Risk-Aware Decision Making and Dynamic Programming.
  B. Defourny, D. Ernst and L. Wehenkel.
  Selected for oral presentation at the NIPS-08 Workshop on Model Uncertainty and Risk in Reinforcement Learning, Whistler, Canada, 2008.
• Lazy Planning under Uncertainty by Optimizing Decisions on an Ensemble of Incomplete Disturbance Trees.
  B. Defourny, D. Ernst and L. Wehenkel.
  In Recent Advances in Reinforcement Learning, 8th European Workshop, EWRL'08, Lecture Notes in Artificial Intelligence, vol. 5323, pp. 1-14, Springer, 2008.
• High-Dimensional Probability Density Estimation with Randomized Ensembles of Tree Structured Bayesian Networks.
  S. Ammar, P. Leray, B. Defourny and L. Wehenkel.
  In Proceedings of the 4th European Workshop on Probabilistic Graphical Models (PGM 2008), Hirtshals, Denmark, 2008.
• Projecting Generation Decisions Induced by a Stochastic Program on a Family of Supply Curve Functions.
  B. Defourny and L. Wehenkel.
  In 3rd Carnegie Mellon Conference on the Electricity Industry, Pittsburgh PA, 2007.

Information for Students

Useful resources for the courses "Introduction to Stochastic Processes" and "Information and Coding Theory" can be found here (in french).