The importance of the efforts towards integrating the symbolic and connectionist paradigms of artificial intelligence has been widely recognised. Integration may lead to more e...
MAP estimation of Gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. This enabled prior beliefs about the scale, orientat...
Abstract. We present a hybrid machine learning approach for information extraction from unstructured documents by integrating a learned classifier based on the Maximum Entropy Mod...
Cross validation allows models to be tested using the full training set by means of repeated resampling; thus, maximizing the total number of points used for testing and potential...
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...