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» A Family of Data-Parallel Derivations
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97
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ECIR
2007
Springer
15 years 2 months ago
Probabilistic Models for Expert Finding
A common task in many applications is to find persons who are knowledgeable about a given topic (i.e., expert finding). In this paper, we propose and develop a general probabilis...
Hui Fang, ChengXiang Zhai
109
Voted
NIPS
2008
15 years 2 months ago
Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction
We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
Shay B. Cohen, Kevin Gimpel, Noah A. Smith
98
Voted
ESANN
2001
15 years 2 months ago
Transfer functions: hidden possibilities for better neural networks
Abstract. Sigmoidal or radial transfer functions do not guarantee the best generalization nor fast learning of neural networks. Families of parameterized transfer functions provide...
Wlodzislaw Duch, Norbert Jankowski
80
Voted
NIPS
2004
15 years 2 months ago
Binet-Cauchy Kernels
We propose a family of kernels based on the Binet-Cauchy theorem and its extension to Fredholm operators. This includes as special cases all currently known kernels derived from t...
S. V. N. Vishwanathan, Alex J. Smola
WICSA
2001
15 years 2 months ago
Annotating Reusable Software Architectures with Specialization Patterns
An application framework is a collection of classes implementing the shared architecture of a family of applications. It is shown how the specialization interface ("hot spots...
Markku Hakala, Juha Hautamäki, Kai Koskimies,...