CIMPA School 2027
From Statistical Inference to Learning Methods (SILM)
March 15 - 26, 2027 | ENSGMM/UNSTIM - Abomey (Benin)
Programming Sessions
Machine Learning for Censored Data
Implementation of random survival forests, CoxBoost, and DeepSurv using R (packages: survival, randomForestSRC, glmnet) and Python (lifelines, scikit-survival, pycox), hands-on examples: patient survival datasets, ecological survival studies, reliability datasets from engineering.
Instructor: Christian PAROISSIN
Sessions: 1 × 1h30 | Total: 1h30
Machine Learning for Financial Mathematics
Implementation of ML models (regression, neural networks, hybrid models) on financial datasets (stock returns, option prices, etc.) using Python (TensorFlow/PyTorch, Scikit-learn).
Instructor: Gero JUNIKE
Sessions: 1 × 1h30 | Total: 1h30
Making Decisions under Uncertainty
Simulation of stochastic processes and MDPs. Solving example decision problems using dynamic programming. Applying reinforcement learning algorithms to real or simulated datasets using R/Python.
Instructor: Benoite DE SAPORTA
Sessions: 1 × 1h30 | Total: 1h30
Machine Learning and Extreme Value Data
Extreme Value Theory estimation and Machine Learning models for extreme events in finance/insurance using R/Python.
Instructor: El-Hadj DEME
Sessions: 1 × 1h30 | Total: 1h30
Total programming sessions: 6h00
Total duration of programming sessions: 6h00
