We examine a setting in which a buyer wishes to purchase probabilistic information from some agent. The seller must invest effort in order to gain access to the information, and m...
This paper proposes a method for computing fast approximations to support vector decision functions in the field of object detection. In the present approach we are building on an...
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
Zhengzhu Feng, Richard Dearden, Nicolas Meuleau, R...
We introduce a computationally feasible, "constructive" active learning method for binary classification. The learning algorithm is initially formulated for separable cl...
Consider a single machine and a set of jobs that are available for processing at time 0. Job ¡ has a processing time ¢¤£ , a due date ¥¦£ and a weight §¨£ . We consid...