Provide fundamental concepts in probability, including conditional, joint, and marginal distributions. Develop a statistical view of data coming from a probability distribution.

Abstract: In this article, the stabilization problem is investigated for a class of networked control systems with random clock offsets and consecutive packet dropouts. Different from the existing ...

Probability theory is indispensable in computer science: It is at the core of artificial intelligence and machine learning, which require decision making under uncertainty. It is integral to CS theory ...

Operational Laws: Little's Law, response-time law, asymptotic bounds, modification analysis, performance metrics. Markov Chain Theory: both discrete-time and continuous-time, renewal theory, ...

Granular materials-from soils to pharmaceutical powders-exhibit mechanical behavior governed by interaction between solid grains and interstitial fluids. Capillary forces critically control these ...

Abstract: In this article, we introduce and study different dissipativity notions and different turnpike properties for discrete-time stochastic nonlinear optimal control problems. The proposed ...

"Just Relax It" is a cutting-edge Python library designed to streamline the optimization of discrete probability distributions in neural networks, offering a suite of advanced relaxation techniques ...

Finally, the large sample sizes with LSAs provide a statistical power for analyses that allows detection on the individual level of even small effects, even if subsamples of the original population ...