Ensuring sufficient liquidity is one of the key challenges for designers of prediction markets. Various market making algorithms have been proposed in the literature and deployed ...
Abstract— Research on numerical solution methods for partially observable Markov decision processes (POMDPs) has primarily focused on discrete-state models, and these algorithms ...
— A series of kinodynamic sampling-based planners have appeared over the last decade to deal with high dimensional problems for robots with realistic motion constraints. Yet, ofï...
(The original conference version of this paper mischaracterizes the contributions of the current authors, relative to the contributions of Keogh et al. [11, 12]. We would like to ...
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...