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NIPS
2004
14 years 29 days ago
Discrete profile alignment via constrained information bottleneck
Amino acid profiles, which capture position-specific mutation probabilities, are a richer encoding of biological sequences than the individual sequences themselves. However, profi...
Sean O'Rourke, Gal Chechik, Robin Friedman, Eleaza...
NIPS
2004
14 years 29 days ago
Hierarchical Bayesian Inference in Networks of Spiking Neurons
There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open quest...
Rajesh P. N. Rao
NIPS
2004
14 years 29 days ago
Mass Meta-analysis in Talairach Space
We provide a method for mass meta-analysis in a neuroinformatics database containing stereotaxic Talairach coordinates from neuroimaging experiments. Database labels are used to g...
Finn Årup Nielsen
NIPS
2004
14 years 29 days 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
2004
14 years 29 days ago
Stable adaptive control with online learning
Learning algorithms have enjoyed numerous successes in robotic control tasks. In problems with time-varying dynamics, online learning methods have also proved to be a powerful too...
Andrew Y. Ng, H. Jin Kim
NIPS
2004
14 years 29 days ago
Detecting Significant Multidimensional Spatial Clusters
Assume a uniform, multidimensional grid of bivariate data, where each cell of the grid has a count ci and a baseline bi. Our goal is to find spatial regions (d-dimensional rectang...
Daniel B. Neill, Andrew W. Moore, Francisco Pereir...
NIPS
2004
14 years 29 days ago
Optimal sub-graphical models
Mukund Narasimhan, Jeff A. Bilmes
NIPS
2004
14 years 29 days ago
Kernels for Multi--task Learning
This paper provides a foundation for multi
Charles A. Micchelli, Massimiliano Pontil
27
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NIPS
2004
14 years 29 days ago
Multiple Relational Embedding
We describe a way of using multiple different types of similarity relationship to learn a low-dimensional embedding of a dataset. Our method chooses different, possibly overlappin...
Roland Memisevic, Geoffrey E. Hinton
NIPS
2004
14 years 29 days ago
Common-Frame Model for Object Recognition
A generative probabilistic model for objects in images is presented. An object consists of a constellation of features. Feature appearance and pose are modeled probabilistically. ...
Pierre Moreels, Pietro Perona