In this paper we present lessons learned in the Evaluating Predictive Uncertainty Challenge. We describe the methods we used in regression challenges, including our winning method ...
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 d...
We propose a system to calculate the spatial distortion in 3-D images based on the shooting, display, and viewing conditions. It can be used to predict the extent of the perceived ...
Probabilistic models of languages are fundamental to understand and learn the profile of the subjacent code in order to estimate its entropy, enabling the verification and predicti...
— We propose a new one-shot collaborative filtering method. In contrast to the conventional methods, which predict unobserved ratings individually and independently, our method ...