Pointwise consistent, feasible procedures for estimating contemporaneous linear causal structure from time series data have been developed using multiple conditional independence ...
We connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to ano...
In this study, a support vector machine (SVM) classifies real world data of cytogenetic signals measured from fluorescence in-situ hybridization (FISH) images in order to diagnose...
In this paper we explore private computation built on vector addition and its applications in privacypreserving data mining. Vector addition is a surprisingly general tool for imp...
Markov Random Field (MRF) models with potentials learned from the data have recently received attention for learning the low-level structure of natural images. A MRF provides a pri...