Concept

Learning to rank

Publications associées (133)

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Perspectives for Rank Aggregation within Scientific Publication Databases

Martin Rajman, Martin Veselý

Ranking in scientific publication databases involves a variety of additional resources that are usually not applied in standard general purpose search engines. Moreover, community-specific expectations of users influence the perception of the adequacy of r ...

2008

Keypoint Signatures for Fast Learning and Recognition

Pascal Fua, Vincent Lepetit, Michael Calonder

Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the training itself is usually relatively slow and performed offline. Although methods hav ...

2008

Stationary Features and Cat Detection

François Fleuret

Most discriminative techniques for detecting instances from object categories in still images consist of looping over a partition of a pose space with dedicated binary classifiers. The efficiency of this strategy for a complex pose, i.e., for fine-grained ...

IDIAP2007

A Thousand Words in a Scene

Daniel Gatica-Perez, Jean-Marc Odobez, Pedro Manuel Da Silva Quelhas

This paper presents a novel approach for visual scene modeling and classification, investigating the combined use of text modeling methods and local invariant features. Our work attempts to elucidate (1) whether a text-like \emph{bag-of-visterms} represent ...

2007

Web Text Retrieval with a P2P Query-Driven Index

Karl Aberer, Martin Rajman, Vinh Toan Luu, Ivana Podnar, Gleb Skobeltsyn

In this paper, we present a query-driven indexing/retrieval strategy for efficient full text retrieval from large document collections distributed within a structured P2P network. Our indexing strategy is based on two important properties: (1) the generate ...

2007

Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

Pedro Manuel Da Silva Quelhas

The ever increasing number of digital images in both public and private collections urges on the need for generic image content analysis systems. These systems need to be capable to capture the content of images from both scenes and objects, in a compact w ...

École Polytechnique Fédérale de Lausanne2007

Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

Pedro Manuel Da Silva Quelhas

EPFL2007

CLEF2007 Image Annotation Task: an SVM-based Cue Integration Approach

Barbara Caputo, Tatiana Tommasi

This paper presents the algorithms and results of our participation to the medical image annotation task of ImageCLEFmed 2007. We proposed, as a general strategy, a multi-cue approach where images are represented both by global and local descrip- tors, so ...

2007

Prior Knowledge in Kernel Methods

Alexei Pozdnoukhov

Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...

École Polytechnique Fédérale de Lausanne2006

Prior knowledge in Kernel methods

Alexei Pozdnoukhov

EPFL2006