Talk today at Statify by Eugène Berta from Sierra Team. Lots of nice stuff on calibration, isotonic regression, and beautiful ternary plots :-) Always good to see former students do so well in research! Paper: proceedings.mlr.press/v238/berta24a.…

What if we have been doing early stopping wrong all along? When you break the validation loss into two terms, calibration and refinement you can make the simplest (efficient) trick to stop training in a smarter position Eugène Berta David Holzmüller Michael Jordan Francis Bach

Backward conformal prediction: Instead of fixing the desired coverage level α, it instead fixes a desired constraint rule that (for instance) dictates the prediction set size. So depending on the setup, the α might be adapted instead. arxiv.org/abs/2505.13732

*Rethinking Early Stopping: Refine, Then Calibrate* by Eugène Berta Leshem (Legend) Choshen 🤖🤗 David Holzmüller Francis Bach Doing early stopping on the "refinement loss" (original loss modulo calibration loss) is beneficial for both accuracy and calibration. arxiv.org/abs/2501.19195

Big thanks to the COLT 2025 organizers for an awesome event in Lyon! Here are the slides from my keynote this morning in case you’re curious about the references I mentioned: di.ens.fr/~fbach/fbach_o…

A great talk about a great paper, check it out 👇

COLT Workshop on Predictions and Uncertainty was a banger! I was lucky to present our paper "Minimum Volume Conformal Sets for Multivariate Regression", alongside my colleague Eugène Berta and his awsome work on calibration. Big thanks to the organizers! #ConformalPrediction

What if AI isn’t about building solo geniuses, but designing social systems? Michael Jordan advocates blending ML, economics, and uncertainty management to prioritize social welfare over mere prediction. A must-read rethink. arxiv.org/abs/2507.06268…

Happy to share the result of a great collaboration with my friend and colleague, the amazing Sacha Braun! A terrific summer read for anyone interested in conformal predicition 👇