A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
—The paper presents a methodology that combines statistical learning with constraint optimization by locally optimizing Radio Resource Management (RRM) or system parameters of po...
Moazzam Islam Tiwana, Zwi Altman, Berna Sayra&cced...
Semantic 3D models of buildings encode the geometry as well as the identity of key components of a facility, such as walls, floors, and ceilings. Manually constructing such a mode...
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...