Symmetry-breaking in constraint satisfaction problems (CSPs) is a well-established area of AI research which has recently developed strong interactions with symbolic computation, i...
Training recurrent neural networks is hard. Recently it has however been discovered that it is possible to just construct a random recurrent topology, and only train a single linea...
Benjamin Schrauwen, David Verstraeten, Jan M. Van ...
A method based on computer vision technologies is presented to achieve the function that the simulated motion in sport simulation system and the motion in sport video are presente...
Abstract. Details of a new technique for obtaining rigorous results concerning the global dynamics of nonlinear systems is described. The technique abstract existence results based...
Many non-cooperative settings that could potentially be studied using game theory are characterized by having very large strategy spaces and payoffs that are costly to compute. Be...