Data-driven array architectures seem to be important alternatives for coarse-grained reconfigurable computing platforms. Their use has provided performance improvements over micro...
We present the design and evaluation of Panoramic, a tool that enables end-users to specify and verify an important family of complex location events. Our approach aims to reduce o...
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...
Background: Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been deve...
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...