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CIKM
2008
Springer
13 years 10 months ago
Passage relevance models for genomics search
We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of t...
Jay Urbain, Ophir Frieder, Nazli Goharian
NIPS
1997
13 years 10 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
RE
1997
Springer
14 years 24 days ago
Requirements Models in Context
The field of requirements engineering emerges out of tradition of research and engineering practice that stresses rtance of generalizations and abstractions. abstraction is essent...
Colin Potts
QUESTA
2006
94views more  QUESTA 2006»
13 years 8 months ago
Modeling teletraffic arrivals by a Poisson cluster process
In this paper we consider a Poisson cluster process N as a generating process for the arrivals of packets to a server. This process generalizes in a more realistic way the infinite...
Gilles Faÿ, Bárbara González-Ar...
ACL
2006
13 years 10 months ago
Minimum Risk Annealing for Training Log-Linear Models
When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
David A. Smith, Jason Eisner