In Nearest Rectangle (NR) learning, training instances are generalized into hyperrectangles and a query is classified according to the class of its nearest rectangle. The method ha...
We present a new class of perceptron-like algorithms with margin in which the "effective" learning rate, defined as the ratio of the learning rate to the length of the we...
In this article, I will consider Markov Decision Processes with two criteria, each defined as the expected value of an infinite horizon cumulative return. The second criterion is e...
Abstract. We propose a novel active learning strategy based on the compression framework of [9] for label ranking functions which, given an input instance, predict a total order ov...