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 ...
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...
Given an arbitrary finite sequence of vectors in a finite–dimensional Hilbert space, we describe an algorithm, which computes a Parseval frame for the subspace generated by the...
In this paper we consider the problem of describing the action being performed by human figures in still images. We will attack this problem using an unsupervised learning approac...
Greg Mori, Hao Jiang, Mark S. Drew, Yang Wang 0003...
The RKLT is a lossless approximation to the KLT, and has been recently employed for progressive lossy-to-lossless coding of hyperspectral images. Both yield very good coding perfo...