In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
We propose a new learning algorithm for the set covering machine and a tight data-compression risk bound that the learner can use for choosing the appropriate tradeoff between the ...
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 examine the set covering machine when it uses data-dependent half-spaces for its set of features and bound its generalization error in terms of the number of training errors an...
Mario Marchand, Mohak Shah, John Shawe-Taylor, Mar...