This study examines a selection of off-the-shelf forecasting and forecast combination algorithms with a focus on assessing their practical relevance by drawing conclusions for non-...
Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application ...
Image retrieval with relevance feedback suffers from the small sample problem. Recently, SVM active learning has been proposed to tackle this problem, showing promising results. H...
A fundamental problem for case-based reasoning systems is how to select relevant prior cases. Numerous strategies have been developed for determining the similarity of prior cases,...
In this paper, we design recommender systems for weblogs based on the link structure among them. We propose algorithms based on refined random walks and spectral methods. First, w...