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arXiv · 2506.11848

In Defense of Defensive Forecasting

Juan Carlos Perdomo·Benjamin Recht
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Abstract

This tutorial provides a survey of algorithms for Defensive Forecasting, where predictions are derived not by prognostication but by correcting past mistakes. Pioneered by Vovk, Defensive Forecasting frames the goal of prediction as a sequential game, and derives predictions to minimize metrics no matter what outcomes occur. We present an elementary introduction to this general theory and derive simple, near-optimal algorithms for online learning, calibration, prediction with expert advice, and online conformal prediction.

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BibTeXRIS

Juan Carlos Perdomo, Benjamin Recht. 2025-06-13. In Defense of Defensive Forecasting. https://arxiv.org/abs/2506.11848

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