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Online Algorithm for Aggregating Experts' Predictions with Unbounded Quadratic Loss

arXiv 2501.06505 ↗First posted 11 Jan 2025cs.LGcited by 0

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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.

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.

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3 of 7 references.

References · 3

  1. 2019Introduction to Online Convex Optimizationcited by 803
  2. 2013Follow the Leader If You Can, Hedge If You Mustcited by 70
  3. 2019Mixability of Integral Losses: a Key to Efficient Online Aggregation of Functional and Probabilistic Forecastscited by 7

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