In a traditional information retrieval system, it is assumed that queries can be posed about any topic. In reality, a large fraction of web queries are posed about a relatively sm...
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...
This work presents a general rank-learning framework for passage ranking within Question Answering (QA) systems using linguistic and semantic features. The framework enables query...
Matthew W. Bilotti, Jonathan L. Elsas, Jaime G. Ca...
We introduce a new plan repair method for problems cast as Mixed Integer Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the ...
Emmanuel Rachelson, Ala Ben Abbes, Sebastien Dieme...