In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
The problem of test generation belongs to the class of NP-complete problems and it is becoming more and more di cult as the complexity of VLSI circuits increases, and as long as e...
Dilip Krishnaswamy, Michael S. Hsiao, Vikram Saxen...
We present worst case bounds for the learning rate of a known prediction method that is based on hierarchical applications of binary context tree weighting (CTW) predictors. A heu...
Sequential algorithms of active learning based on the estimation of the level sets of the empirical risk are discussed in the paper. Localized Rademacher complexities are used in ...
Model selection by the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estima...