Diffusion wavelets are a fast multiscale framework for the analysis of functions on discrete (or discretized continuous) structures like graphsâ€¦Â (More)

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2010

2010

- Ho Yan Suen, Wing Cheong Lau, On-Ching Yue
- 2010 IEEE International Conference onâ€¦
- 2010

Web access logs contain information which can be converted to represent the access history of individual users. A large number ofâ€¦Â (More)

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2009

2009

- Salma Essafi, Georg Langs, Nikos Paragios
- 2009 IEEE 12th International Conference onâ€¦
- 2009

In this paper, we propose a novel representation of prior knowledge for image segmentation, using diffusion wavelets that canâ€¦Â (More)

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2009

2009

- Salma Essafi, Georg Langs, Nikos Paragios
- MICCAI
- 2009

We propose a method for the segmentation of medical images based on a novel parameterization of prior shape knowledge and aâ€¦Â (More)

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2009

2009

Many machine learning data sets are embedded in high-dimensional spaces, and require some type of dimensionality reduction toâ€¦Â (More)

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2007

2007

- Marie Wild
- CAIP
- 2007

Austrian Research Centers GmbH smart systems Division Donau City Str. 1, 1220 Vienna, Austria www.smart-systems.at Motivationâ€¦Â (More)

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2006

2006

We present a novel hierarchical framework for solving Markov decision processes (MDPs) using a multiscale method called diffusionâ€¦Â (More)

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2005

2005

Recent work by some of the authors presented a novel construction of a multiresolution analysis on manifolds and graphs, actedâ€¦Â (More)

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Highly Cited

2005

Highly Cited

2005

- Sridhar Mahadevan, Mauro Maggioni
- NIPS
- 2005

We investigate the problem of automatically constructing efficient representations or basis functions for approximating valueâ€¦Â (More)

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Highly Cited

2004

Highly Cited

2004

We present a multiresolution construction for efficiently computing, compressing and applying large powers of operators that haveâ€¦Â (More)

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2004

2004

Diffusion wavelets can be constructed on manifolds, graphs and allow an efficient multiscale representation of powers of theâ€¦Â (More)

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