In this work, we address investment decisions in production systems by using real options. As is standard in literature, the stochastic variable is assumed to be normally distribu...
Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Ba...
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
In this paper, we focus on reliability, one of the most fundamental and important challenges, in the nanoelectronics environment. For a processor architecture based on the unreliab...
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...