Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
Novelty detection is a machine learning technique which identifies new or unknown information in large data sets. We present our current work on the construction of a new novelty...
Simon J. Haggett, Dominique F. Chu, Ian W. Marshal...
In this work, a generalized method for learning from sequence of unlabelled data points based on unsupervised order-preserving regression is proposed. Sequence learning is a funda...
We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
Psychophysical studies have shown that humans actively exploit temporal information such as contiguity of images in object recognition. We have recently developed a recognition sy...
Arnulf B. A. Graf, Christian Wallraven, Heinrich H...