We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Montele...
We describe a discriminatively trained sequence alignment model based on the averaged perceptron. In common with other approaches to sequence modeling using perceptrons, and in co...
In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multila...
BIC criterion is widely used by the neural-network community for model selection tasks, although its convergence properties are not always theoretically established. In this paper...
Abstract. Multi-layer perceptrons (MLPs) have been widely used in classification and regression task. How to improve the training speed of MLPs has been an interesting field of res...