Fault trees provide a graphical and logical framework for analyzing the reliability of systems. A fault tree provides a conceptually simple modeling framework to represent the sys...
Ragavan Manian, Joanne Bechta Dugan, David Coppit,...
We give a new model of learning motivated by smoothed analysis (Spielman and Teng, 2001). In this model, we analyze two new algorithms, for PAC-learning DNFs and agnostically learn...
Adam Tauman Kalai, Alex Samorodnitsky, Shang-Hua T...
Fault tree analysis is a traditional and well-established technique for analyzing system design and robustness. Its purpose is to identify sets of basic events, called cut sets, wh...
Marco Bozzano, Alessandro Cimatti, Francesco Tappa...
This paper introduces a new method using dyadic decision trees for estimating a classification or a regression function in a multiclass classification problem. The estimator is bas...
We present new results on the well-studied problem of learning DNF expressions. We prove that an algorithm due to Kushilevitz and Mansour [13] can be used to weakly learn DNF form...
Avrim Blum, Merrick L. Furst, Jeffrey C. Jackson, ...