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» Learning Measurement Models for Unobserved Variables
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CVPR
2011
IEEE
14 years 5 months ago
Modeling the joint density of two images under a variety of transformations
We describe a generative model of the relationship between two images. The model is defined as a factored threeway Boltzmann machine, in which hidden variables collaborate to deļ...
Joshua Susskind, Roland Memisevic, Geoffrey Hinton...
RECOMB
2000
Springer
15 years 1 months ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...
SODA
2000
ACM
85views Algorithms» more  SODA 2000»
14 years 10 months ago
Improved bounds on the sample complexity of learning
We present a new general upper bound on the number of examples required to estimate all of the expectations of a set of random variables uniformly well. The quality of the estimat...
Yi Li, Philip M. Long, Aravind Srinivasan
BMVC
2010
14 years 7 months ago
Joint Modeling of Algorithm Behavior and Image Quality for Algorithm Performance Prediction
In this paper, we propose a framework for predicting the performance of a vision algorithm given the input image or video so as to maximize the algorithm's ability to provide...
Apurva Gala, Shishir Shah
RECOMB
2004
Springer
15 years 9 months ago
Modeling and Analysis of Heterogeneous Regulation in Biological Networks
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Irit Gat-Viks, Amos Tanay, Ron Shamir