We propose a new approach for reinforcement learning in problems with continuous actions. Actions are sampled by means of a diffusion tree, which generates samples in the continuou...
Christian Vollmer, Erik Schaffernicht, Horst-Micha...
Click data captures many users’ document preferences for a query and has been shown to help significantly improve search engine ranking. However, most click data is noisy and of...
In this paper, we attempt to improve the effectiveness and the efficiency of query-dependent link-based ranking algorithms such as HITS, MAX and SALSA. All these ranking algorith...
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
Rather than the difficulties of highly non-linear and non-Gaussian observation process and the state distribution in single target tracking, the presence of a large, varying number...