Learning the underlying model from distributed data is often useful for many distributed systems. In this paper, we study the problem of learning a non-parametric model from distr...
There is an increased dominance of intra-die process variations, creating a need for an accurate and fast statistical timing analysis. Most of the recent proposed approaches assum...
Statistical language models estimate the probability of a word occurring in a given context. The most common language models rely on a discrete enumeration of predictive contexts ...
John Blitzer, Kilian Q. Weinberger, Lawrence K. Sa...
This paper proposes a stochastic voting for testing a large number of Web Services (WS) under group testing. In the future, a large number of WS will be available and they need to...
Wei-Tek Tsai, Dawei Zhang, Raymond A. Paul, Yinong...
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, ...