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Robust Discriminative Clustering with Sparse Regularizers

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Low-rank Matrix Approximation Using Point-wise Operators

Arash Amini, Amin Karbasi

Extracting low dimensional structure from high dimensional data arises in many applications such as machine learning, statistical pattern recognition, wireless sensor networks, and data compression. If the data is restricted to a lower dimensional subspace ...

Institute of Electrical and Electronics Engineers2012

Unsupervised Change Detection via Hierarchical Support Vector Clustering

Jean-Philippe Thiran, Devis Tuia, Volker Gass, Frank Grégoire Jean de Morsier, Maurice Borgeaud

When dealing with change detection problems, information about the nature of the changes is often unavailable. In this paper we propose a solution to perform unsupervised change detection based on nonlinear support vector clustering. We build a series of n ...

2012

Hypergraph Clustering for Better Network Traffic Inspection

Boi Faltings, Li Pu

Networked computing environments are subject to configuration errors, unauthorized users, undesired activities and attacks by malicious software. These can be detected by monitoring network traffic, but network administrators are overwhelmed by the amount ...

2011

On the Relation of Slow Feature Analysis and Laplacian Eigenmaps

The past decade has seen a rise of interest in Laplacian eigenmaps (LEMs) for nonlinear dimensionality reduction. LEMs have been used in spectral clustering, in semisupervised learning, and for providing efficient state representations for reinforcement le ...

Massachusetts Institute of Technology Press2011

Discovering Human Places of Interest from Multimodal Mobile Phone Data

Daniel Gatica-Perez

In this paper, a new framework to discover places-of-interest from multimodal mobile phone data is presented. Mobile phones have been used as sensors to obtain location information from usersâ€™ real lives. Two levels of clustering are used to obtain place ...

2010

Analysing the temporal dynamics of model performance for hydrological models

Bettina Schaefli

The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can in ...

European Geosciences Union2009

Geometry-aware analysis of high-dimensional visual information sets

Effrosyni Kokiopoulou

Over the past few decades we have been experiencing a data explosion; massive amounts of data are increasingly collected and multimedia databases, such as YouTube and Flickr, are rapidly expanding. At the same time rapid technological advancements in mobil ...

EPFL2009

A Clustering Method Based on Soft Learning of Model (Prototype) and Dissimilarity Metrics

Arash Arami

Many clustering methods are designed for especial cluster types or have good performance dealing with particular size and shape of clusters. The main problem in this connection is how to define a similarity (or dissimilarity) criterion to make an algorithm ...

Springer-Verlag2009

Flickr Hypergroups

Daniel Gatica-Perez, Radu Andrei Negoescu

The amount of multimedia content available online constantly increases, and this leads to problems for users who search for content or similar communities. Users in Flickr often self-organize in user communities through Flickr Groups. These groups are part ...

2009

Flickr Hypergroups

Daniel Gatica-Perez, Radu Andrei Negoescu

Idiap2009