1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Learning Universal Predictors
Jordi Grau-Moya, Tim Genewein, Marcus Hutter +8
Meta-learning has emerged as a powerful approach to train neural networks to learn new tasks quickly from limited data. Broad exposure to different tasks leads to versatile represe…
cs.LG2023
Hierarchical Partitioning Forecaster
Christopher Mattern
In this work we consider a new family of algorithms for sequential prediction, Hierarchical Partitioning Forecasters (HPFs). Our goal is to provide appealing theoretical - regret g…
cs.IT2015★ 1 cited
On Probability Estimation by Exponential Smoothing
Christopher Mattern
Probability estimation is essential for every statistical data compression algorithm. In practice probability estimation should be adaptive, recent observations should receive a hi…