We consider a memory allocation problem. This problem can be modeled as a version of bin packing where items may be split, but each bin may contain at most two (parts of) items. T...
Competitive on-line prediction (also known as universal prediction of individual sequences) is a strand of learning theory avoiding making any stochastic assumptions about the way...
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
Consider a hidden Markov chain obtained as the observation process of an ordinary Markov chain corrupted by noise. Zuk, et. al. [13, 14] showed how, in principle, one can explicit...
Quantile smoothing splines provide nonparametric estimation of conditional quantile functions. Like other nonparametric smoothing techniques, the choice of smoothing parameters co...