# Online Algorithm for Aggregating Experts' Predictions with Unbounded Quadratic Loss

arXiv: https://arxiv.org/abs/2501.06505 · HTML: https://mlsanity.com/paper/2501.06505/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 7 references that are in the map.
- First posted on arXiv 11 Jan 2025.

## Builds on (most cited first, 3 of 3)

- [Introduction to Online Convex Optimization](https://mlsanity.com/paper/1909.05207/) (2019)
- [Follow the Leader If You Can, Hedge If You Must](https://mlsanity.com/paper/1301.0534/) (2013)
- [Mixability of Integral Losses: a Key to Efficient Online Aggregation of Functional and Probabilistic Forecasts](https://mlsanity.com/paper/1912.07048/) (2019)

## Abstract (arXiv)

We consider the problem of online aggregation of expert predictions with the quadratic loss function. We propose an algorithm for aggregating expert predictions which does not require a prior knowledge of the upper bound on the losses. The algorithm is based on the exponential reweighing of expert losses.