Learning the common structure shared by a set of supervised tasks is an important practical and theoretical problem. Knowledge of this structure may lead to better generalization ...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
Shortage of manually labeled data is an obstacle to supervised relation extraction methods. In this paper we investigate a graph based semi-supervised learning algorithm, a label ...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...
Abstract. We present experimental results about learning function values (i.e. Bellman values) in stochastic dynamic programming (SDP). All results come from openDP (opendp.sourcef...
The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrateworst-case upper bounds on the absolute loss for the perceptron algorithm and ...
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...