Approximate Bayesian Computation (ABC) methods can be used in situations where the evaluation of the likelihood is computationally prohibitive. They are thus ideally suited for analyzing the complex ...

We devise an algorithm for solving the infinite-dimensional linear programs that arise from general deterministic semi-Markov decision processes on Borel spaces. The algorithm constructs a sequence of ...

Due to the NP -hardness of many machine learning problems such as clustering, decision tree, and neural network, one primary belief is that solving ML problems to global optimality is computationally ...

Picture this: a self-driving car smoothly navigating treacherous mountain roads with consecutive hairpin turns – a scenario that would challenge even the most experienced human drivers. This vision is ...