Concept

Learning to rank

Related publications (133)

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Towards semi-supervised learning of semantic spatial concepts for mobile robots

Barbara Caputo, Jesús Martínez Gómez

The ability of building robust semantic space representations of environments is crucial for the development of truly autonomous robots. This task, inherently connected with cognition, is traditionally achieved by training the robot with a supervised learn ...

2011

Dynamic Quantification of Activity Recognition Capabilities in Opportunistic Systems

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha

Opportunistic activity and context recognition systems draw from the characteristic to use sensing devices according to a recognition goal at runtime that just happen to be available instead of pre-defining them at the design time of the system. Whenever a ...

2011

A Speech-based Just-in-Time Retrieval System using Semantic Search

Philip Neil Garner, Andrei Popescu-Belis, Majid Yazdani

The Automatic Content Linking Device is a just-in-time document retrieval system which monitors an ongoing conversation or a monologue and enriches it with potentially related documents, including multimedia ones, from local repositories or from the Intern ...

2011

Comparison-Based Optimizers Need Comparison-Based Surrogates

Ilya Loshchilov

Taking inspiration from approximate ranking, this paper nvestigates the use of rank-based Support Vector Machine as surrogate model within CMA-ES, enforcing the invariance of the approach with respect to monotonous transformations of the fitness function. ...

2010

Using Bibliographic Knowledge for Ranking in Scientific Publication Databases

Martin Rajman, Martin Veselý

Document ranking for scientific publications involves a variety of specialized resources (e.g. author or citation indexes) that are usually difficult to use within standard general purpose search engines that usually operate on large-scale heterogeneous do ...

IOS2008

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 ...

2008

Machine learning for information retrieval

David Grangier

In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...

EPFL2008

Machine Learning for Information Retrieval

David Grangier

École Polytechnique Fédérale de Lausanne2008

Machine Learning for Information Retrieval

David Grangier

IDIAP2008

Discriminative cue integration for medical image annotation

Barbara Caputo, Tatiana Tommasi

Automatic annotation of medical images is an increasingly important tool for physicians in their daily activity. Hospitals nowadays produce an increasing amount of data. Manual annotation is very costly and prone to human mistakes. This paper proposes a mu ...

2008