Publications associées à Weak supervision

Semi-Supervised Novelty Detection using SVM entire solution path

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

Very often, the only reliable information available to perform change detection is the description of some unchanged regions. Since sometimes these regions do not contain all the relevant information to identify their counterpart (the changes), we consider ...

Institute of Electrical and Electronics Engineers2013

Intrusion Detection in MANET Using Classification Algorithms: The Effects of Cost and Model Selection

Christos Dimitrakakis, Aikaterini Mitrokotsa

Intrusion detection is frequently used as a second line of defense in Mobile Ad-hoc Networks (MANETs). In this paper we examine how to properly use classification methods in intrusion detection for MANETs. In order to do so we evaluate five supervised clas ...

Elsevier2013

Multisensor Change Detection with Nonlinear Canonical Correlation

Devis Tuia, Frank Grégoire Jean de Morsier

The analysis of multi-modal and multi-sensor images is nowadays of paramount importance for Earth Observation (EO) applications. There exist a variety of methods that aim at fusing the different sources of information to obtain a compact representation of ...

2013

Semi-Supervised and Unsupervised Novelty Detection using Nested Support Vector Machines

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

Very often in change detection only few labels or even none are available. In order to perform change detection in these extreme scenarios, they can be considered as novelty detection problems, semi-supervised (SSND) if some labels are available otherwise ...

Ieee2012

Supervised and unsupervised Web-based language model domain adaptation

Petr Motlicek, John David Scott Dines

Domain language model adaptation consists in re-estimating probabilities of a baseline LM in order to better match the specifics of a given broad topic of interest. To do so, a common strategy is to retrieve adaptation texts from the Web based on a given d ...

2012

Supervised and unsupervised Web-based language model domain adaptation

Petr Motlicek, John David Scott Dines

Idiap2012

Unsupervised change detection with kernels

Devis Tuia

In this letter, an unsupervised kernel-based approach to change detection is introduced. Nonlinear clustering is utilized to partition in two a selected subset of pixels representing both changed and unchanged areas. Once the optimal clustering is obtained ...

Ieee-Inst Electrical Electronics Engineers Inc2012

Clustering with Multi-Layer Graphs: A Spectral Perspective

Pascal Frossard, Pierre Vandergheynst, Xiaowen Dong

Observational data usually comes with a multimodal nature, which means that it can be naturally represented by a multi-layer graph whose layers share the same set of vertices (users) with different edges (pairwise relationships). In this paper, we address ...

Institute of Electrical and Electronics Engineers2012

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Weak supervision

Semi-Supervised Novelty Detection using SVM entire solution path

Intrusion Detection in MANET Using Classification Algorithms: The Effects of Cost and Model Selection

Multisensor Change Detection with Nonlinear Canonical Correlation

Active Learning: Any Value for Classification of Remotely Sensed Data?

Semi-Supervised and Unsupervised Novelty Detection using Nested Support Vector Machines

Supervised and unsupervised Web-based language model domain adaptation

Supervised and unsupervised Web-based language model domain adaptation

Unsupervised change detection with kernels

Remote sensing image segmentation by active queries

Clustering with Multi-Layer Graphs: A Spectral Perspective

Graph Chatbot

Chattez avec Graph Search

Semi-Supervised and Unsupervised Novelty Detection using Nested Support Vector Machines

Remote sensing image segmentation by active queries

Clustering with Multi-Layer Graphs: A Spectral Perspective

Supervised and unsupervised Web-based language model domain adaptation

Semi-Supervised Novelty Detection using SVM entire solution path

Active Learning: Any Value for Classification of Remotely Sensed Data?

Intrusion Detection in MANET Using Classification Algorithms: The Effects of Cost and Model Selection

Multisensor Change Detection with Nonlinear Canonical Correlation

Supervised and unsupervised Web-based language model domain adaptation

Unsupervised change detection with kernels