We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. Th...
Zach Solan, David Horn, Eytan Ruppin, Shimon Edelm...
Extracting knowledge from unstructured text is a long-standing goal of NLP. Although learning approaches to many of its subtasks have been developed (e.g., parsing, taxonomy induc...
Abstract. Humans have the remarkable ability to generalize from binocular to monocular figure-ground segmentation of complex scenes. This is clearly evident anytime we look at a p...
Brian Mingus, Trent Kriete, Seth A. Herd, Dean Wya...
The challenge of recovering the topology of massive neuronal circuits can potentially be met by high throughput Electron Microscopy (EM) imagery. Segmenting a 3-dimensional stack o...
Daniel Glasner, Tao Hu, Juan Nunez-Iglesias, Lou S...
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to repla...