We study the problem of approximating pseudoBoolean functions by linear pseudo-Boolean functions. Pseudo-Boolean functions generalize ordinary Boolean functions by allowing the fu...
Guoli Ding, Robert F. Lax, Peter P. Chen, Jianhua ...
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...