Many predictive tasks require labeled data to induce classification models. The data labeling
process may have a high cost. Several strategies have been proposed to optimize the …

To save the labeling efforts for training a classification model, we can simultaneously adopt
Active Learning (AL) to select the most informative samples for human labeling, and Semi …

Since each visual feature only reflects a unique characteristic about a 3-dimensional (3D)
model and different visual features have diverse discriminative power in model …

Naturally occurring data have been growing in a huge volume size, which poses a big
challenge to give them high-quality labels to learn a good model. Therefore, it is critical to …

This paper aims to provide high quality tags for digital images according to users' interest. As
there are three main elements in image tag recommendation problem, tensor factorization …

Feature selection and instance selection are dual operations on a data matrix. Feature
selection aims at selecting a subset of relevant and informative features from original feature …

Nowadays images play a crucial role in different fields such as medicine, advertisement,
education and entertainment. Describing images content and retrieving them are important …

Each image in a Content Based Image Retrieval (CBIR) system is represented by its
features such as colour, texture and shape. These three groups of features are stored in the …

With the development of multimedia data, cross-media retrieval has become increasingly
important. It can provide the retrieval results with various types of media at the same time by …

Nous observons que la stratégie d'apprentissage non-agnostique basée sur l'incertitude du
modèle permet un apprentissage plus efficace dans les premières requêtes qu'une stratégie …