• Publications
  • Influence
On Spectral Clustering: Analysis and an algorithm
TLDR
A simple spectral clustering algorithm that can be implemented using a few lines of Matlab is presented, and tools from matrix perturbation theory are used to analyze the algorithm, and give conditions under which it can be expected to do well. Expand
Spectral Hashing
TLDR
The problem of finding a best code for a given dataset is closely related to the problem of graph partitioning and can be shown to be NP hard and a spectral method is obtained whose solutions are simply a subset of thresholded eigenvectors of the graph Laplacian. Expand
From learning models of natural image patches to whole image restoration
  • Daniel Zoran, Yair Weiss
  • Mathematics, Computer Science
  • International Conference on Computer Vision
  • 6 November 2011
TLDR
A generic framework which allows for whole image restoration using any patch based prior for which a MAP (or approximate MAP) estimate can be calculated is proposed and a generic, surprisingly simple Gaussian Mixture prior is presented, learned from a set of natural images. Expand
Constructing free-energy approximations and generalized belief propagation algorithms
TLDR
This work explains how to obtain region-based free energy approximations that improve the Bethe approximation, and corresponding generalized belief propagation (GBP) algorithms, and describes empirical results showing that GBP can significantly outperform BP. Expand
A Closed-Form Solution to Natural Image Matting
TLDR
A closed-form solution to natural image matting that allows us to find the globally optimal alpha matte by solving a sparse linear system of equations and predicts the properties of the solution by analyzing the eigenvectors of a sparse matrix, closely related to matrices used in spectral image segmentation algorithms. Expand
Colorization using optimization
TLDR
This paper presents a simple colorization method that requires neither precise image segmentation, nor accurate region tracking, and demonstrates that high quality colorizations of stills and movie clips may be obtained from a relatively modest amount of user input. Expand
Understanding belief propagation and its generalizations
TLDR
It is shown that BP can only converge to a fixed point that is also a stationary point of the Bethe approximation to the free energy, which enables connections to be made with variational approaches to approximate inference. Expand
Loopy Belief Propagation for Approximate Inference: An Empirical Study
TLDR
This paper compares the marginals computed using loopy propagation to the exact ones in four Bayesian network architectures, including two real-world networks: ALARM and QMR, and finds that the loopy beliefs often converge and when they do, they give a good approximation to the correct marginals. Expand
A Closed-Form Solution to Natural Image Matting
TLDR
A closed-form solution to natural image matting that allows us to find the globally optimal alpha matte by solving a sparse linear system of equations and predicts the properties of the solution by analyzing the eigenvectors of a sparse matrix, closely related to matrices used in spectral image segmentation algorithms. Expand
Generalized Belief Propagation
TLDR
It is shown that BP can only converge to a stationary point of an approximate free energy, known as the Bethe free energy in statistical physics, and generalized belief propagation (GBP) versions of these Kikuchi approximations are derived. Expand
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