Transfer Learning for Linear Regression: a Statistical Test of Gain

no code implementations • 18 Feb 2021 • David Obst, Badih Ghattas, Jairo Cugliari, Georges Oppenheim, Sandra Claudel, Yannig Goude

Transfer learning, also referred as knowledge transfer, aims at reusing knowledge from a source dataset to a similar target one.

regression Transfer Learning

Smooth And Consistent Probabilistic Regression Trees

no code implementations • NeurIPS 2020 • Sami Alkhoury, Emilie Devijver, Marianne Clausel, Myriam Tami, Eric Gaussier, Georges Oppenheim

We propose here a generalization of regression trees, referred to as Probabilistic Regression (PR) trees, that adapt to the smoothness of the prediction function relating input and output variables while preserving the interpretability of the prediction and being robust to noise.

regression

Textual Data for Time Series Forecasting

no code implementations • 25 Oct 2019 • David Obst, Badih Ghattas, Sandra Claudel, Jairo Cugliari, Yannig Goude, Georges Oppenheim

While ubiquitous, textual sources of information such as company reports, social media posts, etc.

Time Series Time Series Forecasting +1