In this contribution, we explore the possibilities of learning in large-scale, multimodal processing systems operating under real-world conditions. Using an instance of a large-sca...
—This paper presents a novel transport protocol, CUSP, specifically designed with complex and dynamic network applications in mind. Peer-to-peer applications benefit in particu...
Wesley W. Terpstra, Christof Leng, Max Lehn, Aleja...
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
— Enriched with more and more intelligent devices modern homes rapidly transform into smart environments. Their growing capabilities enable the implementation of a new generation...
Grzegorz Lehmann, Andreas Rieger, Marco Blumendorf...
Complex networks, such as biological, social, and communication networks, often entail uncertainty, and thus, can be modeled as probabilistic graphs. Similar to the problem of sim...
Michalis Potamias, Francesco Bonchi, Aristides Gio...