In this paper we consider the problem of building a system to predict readability of natural-language documents. Our system is trained using diverse features based on syntax and l...
Rohit J. Kate, Xiaoqiang Luo, Siddharth Patwardhan...
Multi-document summarization aims to distill the most important information from a set of documents to generate a compressed summary. Given a sentence graph generated from a set o...
This paper presents both a semantic and a computational model for multi-agent belief revision. We show that these two models are equivalent but serve different purposes. The seman...
We present a component-based, trainable system for detecting frontal and near-frontal views of faces in still gray images. The system consists of a two-level hierarchy of Support ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
Classic methods for Bayesian inference effectively constrain search to lie within regions of significant probability of the temporal prior. This is efficient with an accurate dyna...
David Demirdjian, Leonid Taycher, Gregory Shakhnar...