In this paper, we applied online neuroevolution to evolve nonplayer characters for The Open Racing Car Simulator (TORCS). While previous approaches allowed online learning with per...
Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
The system presented is a web application designed to aid linguistic research with data collection and online publishing. It is a service mainly for linguists and language experts...
Online learning algorithms have impressive convergence properties when it comes to risk minimization and convex games on very large problems. However, they are inherently sequenti...
Daniel Hsu, Nikos Karampatziakis, John Langford, A...
Online reviews are widely used for purchase decisions. Their trustworthiness is limited, however, by fake reviews. Fortunately, opinions from friends in a social network are more ...
In this paper we introduce a discrete version of the online traveling salesman problem (DOLTSP). We represent the metric space using a weighted graph, where the server is allowed t...
The dynamic marketplace in online advertising calls for ranking systems that are optimized to consistently promote and capitalize better performing ads. The streaming nature of on...
Wei Li 0010, Xuerui Wang, Ruofei Zhang, Ying Cui, ...
Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data ana...
Extreme technology scaling in silicon devices drastically affects reliability, particularly because of runtime failures induced by transistor wearout. Currently available online t...
—It has been widely acknowledged that online file hosting systems within the “cloud” of the Internet have provided valuable services to end users who wish to share files of a...
Fangming Liu, Ye Sun, Bo Li, Baochun Li, Xinyan Zh...
Abstract. In this paper we study distributed online learning of locomotion gaits for modular robots. The learning is based on a stochastic approximation method, SPSA, which optimiz...