We introduce a new bias for rule learning systems. The bias only allows a rule learner to create a rule that predicts class membership if each test of the rule in isolation is pred...
Class imbalance is a ubiquitous problem in supervised learning and has gained wide-scale attention in the literature. Perhaps the most prevalent solution is to apply sampling to t...
We show a sharp dichotomy between systems of identical automata with a symmetric global control whose behavior is easy to predict, and those whose behavior is hard to predict. The...
Samuel R. Buss, Christos H. Papadimitriou, John N....
We describe a new method to predict the tertiary structure of new-fold proteins. Our two-phase approach combines the knowledge-based fragmentpacking with the minimization of a phy...
Jinhui Ding, Elizabeth Eskow, Nelson L. Max, Silvi...
Image auto-annotation is an important open problem in
computer vision. For this task we propose TagProp, a discriminatively
trained nearest neighbor model. Tags of test
images a...
Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek...