Political Analysis, Vol. 26, No. 1 (January 2018), pp. 54-71 (18 pages) Measuring the causal impact of state behavior on outcomes is one of the biggest methodological challenges in the field of ...

Distributed inference when the participants are only machines or electronic devices, e.g., sensors, has been explored extensively in the signal processing and machine learning literature. However, ...

The American Journal of Political Science (AJPS), published four times each year, is one of the most widely-read political science journals in the United States. AJPS is a general journal of political ...

Future applications of national importance, such as healthcare, critical infrastructure, transportation systems, and smart cities, are expected to increasingly rely on machine-learning methods, ...

If program staff suspects you may have used AI tools to complete assignments in ways not explicitly authorized or suspect other violations of the honor code, they will contact you via email. Be sure ...

Probabilistic Sentential Decision Diagrams (PSDDs) are an elegant framework for learning from and reasoning about data. They provide tractable representations of discrete probability distributions ...

ATLANTA--(BUSINESS WIRE)--SC24—SambaNova, the generative AI company offering the most efficient AI chips and fastest models, announces that the U.S. Department of Energy’s (DOE) Argonne National ...

Scientists have confirmed that human brains are naturally wired to perform advanced calculations, much like a high-powered computer, to make sense of the world through a process known as Bayesian ...