We generalize the classical algorithms of Valiant and Haussler for learning conjunctions and disjunctions of Boolean attributes to the problem of learning these functions over arb...
We discuss the use in machine learning of a general type of convex optimisation problem known as semi-definite programming (SDP) [1]. We intend to argue that SDP’s arise quite n...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Multi-instance learning and semi-supervised learning are different branches of machine learning. The former attempts to learn from a training set consists of labeled bags each con...
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...