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

Related publications (102)

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Likelihood estimation of the extremal index

Mária Süveges

The extension of the likelihood method of Süveges (Extremes, 2007) is presented. The extension allows for finding independent clusters of extreme events and determining the range of dependence on extremal levels, and estimate clustering characteristic of t ...

2007

Static impurities in the S=3/2 kagome lattice: Exact diagonalization calculations on small clusters

Frédéric Mila, Bruce Normand

We consider the effects of doping the S=3/2 kagome lattice with static, nonmagnetic impurities. By exact-diagonalization calculations on small clusters, we deduce the local spin correlations and magnetization distribution around a vacancy. As in the S=1/2 ...

2007

Counting pedestrians in video sequences using trajectory clustering

Jean-Philippe Thiran, Gianluca Antonini

In this paper we propose to use clustering methods for automatic counting of pedestrians in video sequences. As input, we consider the output of those detection/ tracking systems that overestimate the number of targets. Clustering techniques are applied to ...

2006

Peer Sharing Behaviour in the eDonkey Network, and Implications for the Design of Server-less File Sharing Systems

Anne-Marie Kermarrec, Sidath Handurukande

In this paper we present an empirical study of a workload gathered by crawling the eDonkey network - a dominant peer-to-peer file sharing system - for over 50 days. We first confirm the presence of some known features, in particular the prevalence of free- ...

2006

Robust audio segmentation

Jitendra Ajmera

Audio segmentation, in general, is the task of segmenting a continuous audio stream in terms of acoustically homogenous regions, where the rule of homogeneity depends on the task. This thesis aims at developing and investigating efficient, robust and unsup ...

EPFL2005

Kernelized Infomax Clustering

We propose a simple information-theoretic clustering approach based on maximizing the mutual information

I(\sfx,y)

between the unknown cluster labels

y

and the training patterns

\sfx

with respect to parameters of specifically constrained encoding dis ...

IDIAP2005

Analysis of a Synonymy Network

Paolo De Los Rios, Jean-Cédric Chappelier, David Gfeller

The purpose of this report is to present the study of a linguistic network based on the relation of synonymy. The network has been extracted from a dictionary of synonyms in French. Due to errors and ambiguities in the data, the synonyms are not always gro ...

2004

Robust Audio Segmentation

Hervé Bourlard, Jitendra Ajmera

IDIAP2004

Robust Audio Segmentation

Hervé Bourlard, Jitendra Ajmera

École Polytechnique Fédérale de Lausanne2004

Making Retrieval Faster Through Document Clustering

David Grangier, Alessandro Vinciarelli

This work addresses the problem of reducing the time between query submission and results output in a retrieval system. The goal is achieved by considering only a database fraction as small as possible during the retrieval process. Our approach is based on ...