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» Inference for Multiplicative Models
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ICSE
2009
IEEE-ACM
15 years 5 months ago
Selective backtracking of model changes
Backtracking is necessary when design alternatives are explored or dead ends are reached. Unfortunately, current approaches support chronological backtracking only (undo or versio...
Iris Groher, Alexander Egyed
NIPS
2001
15 years 8 months ago
Global Coordination of Local Linear Models
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinto...
NIPS
1997
15 years 8 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
BMCBI
2007
125views more  BMCBI 2007»
15 years 7 months ago
Bayesian meta-analysis models for microarray data: a comparative study
Background: With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis...
Erin M. Conlon, Joon J. Song, Anna Liu
ECCV
2006
Springer
16 years 9 months ago
Sparse Flexible Models of Local Features
Abstract. In recent years there has been growing interest in recognition models using local image features for applications ranging from long range motion matching to object class ...
Gustavo Carneiro, David Lowe