We consider the model selection problem for support vector machines applied to binary classification. As the data generating process is unknown, we have to rely on heuristics as mo...
Partially supervised segmentation, that is, segmentation with always incomplete training data has many practical applications in image analysis and retrieval. This paper proposes a...
We suggest a nonparametric framework for unsupervised learning of projection models in terms of density estimation on quantized sample spaces. The objective is not to optimally re...
Content-based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Most of the attention from the research has been focused on indexing t...
Qi Tian, Nicu Sebe, Michael S. Lew, Etienne Loupia...
We propose a new approach to value-directed belief state approximationfor POMDPs. The valuedirected model allows one to choose approximation methods for belief state monitoringtha...