Here are some conferences focused on R taking place in the next few months:

Conduct and Interpret a Canonical Correlation

“Data science is a component of many sciences, including the health and social sciences. Therefore, the tasks of data science are the tasks of those sciences – description, prediction, causal inference. A sometimes overlooked point is that a successful data science requires not only good data and algorithms, but also domain knowledge (including causal knowledge) from its parent sciences.” Miguel A. Hernán, John Hsu, Brian Healy ( July 12, 2018 )

Diagram Generating Function (DGF) The recently-introduced self-learning Monte Carlo method is a general-purpose numerical method that speeds up Monte Carlo simulations by training an effective model to propose uncorrelated configurations in the Markov chain. We implement this method in the framework of continuous time Monte Carlo method with auxiliary field in quantum impurity models. We introduce and train a diagram generating function (DGF) to model the probability distribution of auxiliary field configurations in continuous imaginary time, at all orders of diagrammatic expansion. By using DGF to propose global moves in configuration space, we show that the self-learning continuous-time Monte Carlo method can significantly reduce the computational complexity of the simulation. …

About me

At: Colorado State University Location: Fort Collins, COWeb: www.colostate.eduPosition: Assistant Professor in Industrial and Organizational (IO) Psychology

I noticed this article in the newspaper today:

Amazon SageMaker now comes with a faster Pipe mode implementation, significantly accelerating the speeds at which data can be streamed from Amazon Simple Storage Service (S3) into Amazon SageMaker while training machine learning models.

Contextual Multi-Armed Bandits for Causal Marketing