We introduce in this paper a generalization of the widely used hidden Markov models (HMM's), which we name "structural hidden Markov models" (SHMM). Our approach is ...
Results of neural network learning are always subject to some variability, due to the sensitivity to initial conditions, to convergence to local minima, and, sometimes more dramat...
The Bradley-Terry model for obtaining individual skill from paired comparisons has been popular in many areas. In machine learning, this model is related to multi-class probabilit...
The aim of the presented system is simplification and speedup of the daily pathological examination routine. The system combines telepathology with computer-aided diagnostics algor...
Grigory Begelman, Michael Pechuk, Ehud Rivlin, Edm...
Abstract--The ranking problem has become increasingly important in modern applications of statistical methods in automated decision making systems. In particular, we consider a for...