We use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. Clustering improves...
We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...
Forecasting sequences by expert ensembles generally assumes stationary or near-stationary processes; however, in complex systems and many real-world applications, we are frequentl...
Cosma Rohilla Shalizi, Abigail Z. Jacobs, Aaron Cl...
We present an experiment comparing double exponential smoothing and Kalman filter-based predictive tracking algorithms with derivative free measurement models. Our results show t...
Background: Models for the simulation of metabolic networks require the accurate prediction of enzyme function. Based on a genomic sequence, enzymatic functions of gene products a...
Constantin Bannert, A. Welfle, C. aus dem Spring, ...