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NIPS
2003
13 years 6 months ago
Linear Response for Approximate Inference
Belief propagation on cyclic graphs is an efficient algorithm for computing approximate marginal probability distributions over single nodes and neighboring nodes in the graph. I...
Max Welling, Yee Whye Teh
NIPS
2003
13 years 6 months ago
Extreme Components Analysis
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
Max Welling, Felix V. Agakov, Christopher K. I. Wi...
NIPS
2003
13 years 6 months ago
Learning Near-Pareto-Optimal Conventions in Polynomial Time
We study how to learn to play a Pareto-optimal strict Nash equilibrium when there exist multiple equilibria and agents may have different preferences among the equilibria. We focu...
Xiao Feng Wang, Tuomas Sandholm
NIPS
2003
13 years 6 months ago
Salient Boundary Detection using Ratio Contour
This paper presents a novel graph-theoretic approach, named ratio contour, to extract perceptually salient boundaries from a set of noisy boundary fragments detected in real image...
Song Wang, Toshiro Kubota, Jeffrey Mark Siskind
NIPS
2003
13 years 6 months ago
Self-calibrating Probability Forecasting
In the problem of probability forecasting the learner’s goal is to output, given a training set and a new object, a suitable probability measure on the possible values of the ne...
Vladimir Vovk, Glenn Shafer, Ilia Nouretdinov
NIPS
2003
13 years 6 months ago
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression
Nonlinear filtering can solve very complex problems, but typically involve very time consuming calculations. Here we show that for filters that are constructed as a RBF network ...
Roland Vollgraf, Michael Scholz, Ian A. Meinertzha...
NIPS
2003
13 years 6 months ago
Sequential Bayesian Kernel Regression
We propose a method for sequential Bayesian kernel regression. As is the case for the popular Relevance Vector Machine (RVM) [10, 11], the method automatically identifies the num...
Jaco Vermaak, Simon J. Godsill, Arnaud Doucet
NIPS
2003
13 years 6 months ago
Non-linear CCA and PCA by Alignment of Local Models
We propose a non-linear Canonical Correlation Analysis (CCA) method which works by coordinating or aligning mixtures of linear models. In the same way that CCA extends the idea of...
Jakob J. Verbeek, Sam T. Roweis, Nikos A. Vlassis
NIPS
2003
13 years 6 months ago
Image Reconstruction by Linear Programming
— One way of image denoising is to project a noisy image to the subspace of admissible images derived, for instance by PCA. However, a major drawback of this method is that all p...
Koji Tsuda, Gunnar Rätsch