We propose a generalization of multilabel classification that we refer to as graded multilabel classification. The key idea is that, instead of requesting a yes-no answer to the q...
A major problem in machine learning is that of inductive bias: how to choose a learner's hypothesis space so that it is large enough to contain a solution to the problem bein...
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
We present a faster method of solving optimal planning problems and show that our solution performs up to an order of magnitude faster than Satplan on a variety of problems from t...