Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
We study losses for binary classification and class probability estimation and extend the understanding of them from margin losses to general composite losses which are the compos...
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in both text and image modalities. While the normalization and combination of evi...