In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
We study the effects of various emergent topologies of interaction on the rate of language convergence in a population of communicating agents. The agents generate, parse, and lea...
Developing computational models paves the way to understanding, predicting, and influencing the long-term behavior of genomic regulatory systems. However, several major challenges ...
Ivan Ivanov, Plamen Simeonov, Noushin Ghaffari, Xi...