We propose a metric for surface parameterization specialized to its signal that can be used to create more efficient, high-quality texture maps. Derived from Taylor expansion of s...
Geetika Tewari, John Snyder, Pedro V. Sander, Stev...
Traditional optimizers fail to pick good execution plans, when faced with increasingly complex queries and large data sets. This failure is even more acute in the context of XQuery...
Riham Abdel Kader, Maurice van Keulen, Peter A. Bo...
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
Machine learning techniques are increasingly being used to produce a wide-range of classifiers for complex real-world applications that involve nonuniform testing costs and miscl...
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
Alessandro Lazaric, Marcello Restelli, Andrea Bona...