398 citations · 1.8k across the 163 of their papers we have counts for
11 papers · 1 filter
Robust Inference of Trees
Marco Zaffalon, Marcus Hutter
This paper is concerned with the reliable inference of optimal tree-approximations to the dependency structure of an unknown distribution generating data. The traditional approach…
Universal Learning of Repeated Matrix Games
Jan Poland, Marcus Hutter
We study and compare the learning dynamics of two universal learning algorithms, one based on Bayesian learning and the other on prediction with expert advice. Both approaches have…
Sequential Predictions based on Algorithmic Complexity
Marcus Hutter
This paper studies sequence prediction based on the monotone Kolmogorov complexity Km=-log m, i.e. based on universal deterministic/one-part MDL. m is extremely close to Solomonoff…
Defensive Universal Learning with Experts
Jan Poland, Marcus Hutter
This paper shows how universal learning can be achieved with expert advice. To this aim, we specify an experts algorithm with the following characteristics: (a) it uses only feedba…
Monotone Conditional Complexity Bounds on Future Prediction Errors
Alexey Chernov, Marcus Hutter
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true dis…
Asymptotics of Discrete MDL for Online Prediction
Jan Poland, Marcus Hutter
Minimum Description Length (MDL) is an important principle for induction and prediction, with strong relations to optimal Bayesian learning. This paper deals with learning non-i.i.…