We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...
We provide a framework to exploit dependencies among arms in multi-armed bandit problems, when the dependencies are in the form of a generative model on clusters of arms. We find ...
In inductive logic programming, subsumption is a widely used coverage test. Unfortunately, testing -subsumption is NP-complete, which represents a crucial efficiency bottleneck fo...
We propose a new algorithm for independent component and independent subspace analysis problems. This algorithm uses a contrast based on the Schweizer-Wolff measure of pairwise de...
In many applications, unlabelled examples are inexpensive and easy to obtain. Semisupervised approaches try to utilise such examples to reduce the predictive error. In this paper,...