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 provide a polyhedral description of the conditions for the existence of the maximum likelihood estimate (MLE) for a hierarchical log-linear model. The MLE exists if and only if...
Nicholas Eriksson, Stephen E. Fienberg, Alessandro...
For coded transmission over a memoryless channel, two kinds of mutual information are considered: the mutual information between a code symbol and its noisy observation and the ove...
Ingmar Land, Simon Huettinger, Peter A. Hoeher, Jo...
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
— This paper introduces a Bayesian filter that is specifically designed for counting targets that move outside of the field of view while performing a sensor sweep. Informatio...