3 papers
stat.ML2024
SEMF: Supervised Expectation-Maximization Framework for Predicting Intervals
Ilia Azizi, Marc-Olivier Boldi, Valérie Chavez-Demoulin
This work introduces the Supervised Expectation-Maximization Framework (SEMF), a versatile and model-agnostic approach for generating prediction intervals with any ML model. SEMF e…
stat.AP2019
Intraday Retail Sales Forecast: An Efficient Algorithm for Quantile Additive Modeling
Marc-Olivier Boldi, Valérie Chavez-Demoulin, Olivier Gallay
With the ever increasing prominence of data in retail operations, sales forecasting has become an essential pillar in the efficient management of inventories. When facing high dema…
stat.ME2017
Improving the local scoring algorithm using gradient sampling
Marc-Olivier Boldi, Valérie Chavez-Demoulin
We adapt the gradient sampling algorithm to the local scoring algorithm to solve complex estimation problems based on an optimization of an objective function. This overcomes non-d…