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NIPS
2008
15 years 6 months ago
Structured ranking learning using cumulative distribution networks
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
Jim C. Huang, Brendan J. Frey
CARS
2003
15 years 6 months ago
Does incorrect computer prompting affect human decision making? A case study in mammography
The goal of the data collection and analyses described in this paper was to investigate the effects of incorrect output from a CAD tool on the reliability of the decisions of its ...
Eugenio Alberdi, Andrey Povyakalo, Lorenzo Strigin...
NIPS
2004
15 years 6 months ago
Incremental Algorithms for Hierarchical Classification
We study the problem of hierarchical classification when labels corresponding to partial and/or multiple paths in the underlying taxonomy are allowed. We introduce a new hierarchi...
Nicolò Cesa-Bianchi, Claudio Gentile, Andre...
NIPS
2004
15 years 6 months ago
Expectation Consistent Free Energies for Approximate Inference
We propose a novel a framework for deriving approximations for intractable probabilistic models. This framework is based on a free energy (negative log marginal likelihood) and ca...
Manfred Opper, Ole Winther
NIPS
2003
15 years 6 months ago
Extreme Components Analysis
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
Max Welling, Felix V. Agakov, Christopher K. I. Wi...