Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...
This paper presents a new learning approach for pattern classification applications involving imbalanced data sets. In this approach, a clustering technique is employed to resamp...
Giang Hoang Nguyen, Abdesselam Bouzerdoum, Son Lam...
Biometrics based on electroencephalogram (EEG) signals is an emerging research topic. Several recent results have shown its feasibility and potential for personal identification....
A new learning strategy for object detection is presented.
The proposed scheme forgoes the need to train a collection
of detectors dedicated to homogeneous families of poses,
an...
Karim Ali, Francois Fleuret, David Hasler and Pasc...