Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
Brain-computer interfaces (BCIs) are limited in their applicability in everyday settings by the current necessity to record subjectspecific calibration data prior to actual use of...
Morteza Alamgir, Moritz Grosse-Wentrup, Yasemin Al...
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. Active learning seeks to select the m...
Humans have an amazing ability to perceive depth from a single still image; however, it remains a challenging problem for current computer vision systems. In this paper, we will p...