Jean-Michel Renders

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This work presents a new perspective on characterizing the similarity between elements of a database or, more generally, nodes of a weighted and undirected graph. It is based on a Markov-chain model of random walk through the database. More precisely, we compute quantities (the average commute time, the pseudoinverse of the Laplacian matrix of the graph,(More)
We address the problem of categorising documents using kernel-based methods such as Support Vector Machines. Since the work of Joachims (1998), there is ample experimental evidence that SVM using the standard word frequencies as features yield state-of-the-art performance on a number of benchmark problems. Recently, Lodhi et al. (2002) proposed the use of(More)
We present a geometric view on bilingual lexicon extraction from comparable corpora, which allows to re-interpret the methods proposed so far and identify unresolved problems. This motivates three new methods that aim at solving these problems. Empirical evaluation shows the strengths and weaknesses of these methods, as well as a significant gain in the(More)
This paper discusses the trade-off between accuracy, reliability and computing time in global optimization. Particular compromises provided by traditional methods (Quasi-Newton and Nelder-Mead's simplex methods) and genetic algorithms are addressed and illustrated by a particular application in the field of nonlinear system identification. Subsequently, new(More)
This work presents some general procedures for computing dissimilarities between elements of a database or, more generally, nodes of a weighted, undirected, graph. It is based on a Markov-chain model of random walk through the database. The model assigns transition probabilities to the links between elements, so that a random walker can jump from element to(More)
This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate(More)
This document describes XRCE’s participation to Imageval, more specifically to the mixed Text-Image search. After reviewing stateof-the-art methods to exploit the correlations between texts and images in multimedia retrieval, we will examine the single-media search components and describe how we have combined them in the framework of ImagEval. It appeared(More)
This work presents a new perspective on characterizing the similarity be-<lb>tween elements of a database or, more generally, nodes of a weighted, undi-<lb>rected, graph. It is based on a Markov-chain model of random walk through<lb>the database. More precisely, we compute quantities (the average commute<lb>time, the pseudoinverse of the Laplacian matrix of(More)
The aim of this document is to describe the methods we used in the Patent Image Classification and Image-based Patent Retrieval tasks of the Clef-IP 2011 track. The patent image classification task consisted in categorizing patent images into predefined categories such as abstract drawing, graph, flowchart, table, etc. Our main aim in participating in this(More)