Large software companies have to plan their project portfolio to maximize potential portfolio return and strategic alignment, while balancing various preferences, and considering ...
Active learning techniques have gained popularity in reducing human effort to annotate data instances for inducing a classifier. When faced with large quantities of unlabeled dat...
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
The stream processing characteristics of many embedded system applications in multimedia and networking domains have led to the advent of stream based programming formats. Several ...
We discuss multiclass-multilabel classification problems in which the set of classes is extremely large. Most existing multiclass-multilabel learning algorithms expect to observe ...