In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support Vector Machines have be...
Christian Wallraven, Barbara Caputo, Arnulf B. A. ...
Algorithms based on following local gradient information are surprisingly effective for certain classes of constraint satisfaction problems. Unfortunately, previous local search a...
The development of successful metaheuristic algorithms such as local search for a difficult problems such as satisfiability testing (SAT) is a challenging task. We investigate an ...
Image categorization involves the well known difficulties with different visual appearances of a single object, but introduces also the problem of within-category variation. This ...