If you are like me, you have played the game *SET* and have probably been perplexed at how quickly some people can play the game! Even as the game is quite easy to explain, it takes some time to build various strategies and pattern recognition to play the game effectively. If you have never heard of *SET*, don’t fret because we will soon review its layout. For my final masters project at Texas A&M University, we had the autonomy to research any higher-level mathematical topic and I felt *SET* would be a great venue to tap into some deeper mathematics. Little did I know how truly complex and elegant *SET* really is with connections to combinatorial geometry, finite affine geometry, and vector spaces over finite fields, some of these problems still open in research-level mathematics. All of these topics (and more) are included in a great resource I highly recommend for some summer reading. Check out *The Joy of Set* by McMahon, et al. to dig deeper into what is presented below.

## You're reading: Posts Tagged: high-dimensional geometry

### Information and Inference: new journal with free content for two years

The Institute of Mathematics and its Applications has launched a new journal, *Information and Inference: a Journal of the IMA*. This aims to

publish high quality mathematically-oriented articles, furthering the understanding of the theory, methods of analysis, and algorithms for information and data.

Articles should be written in a way accessible to researchers in the associated topics in pure and applied mathematics, statistics, computer sciences, and electrical engineering. Articles are published in, but not limited to: information theory, statistical inference, network analysis, numerical analysis, learning theory, applied and computational harmonic analysis, probability, combinatorics, signal processing, and high-dimensional geometry.

According to the website, “all content will be free to access for the first two years of publication of the journal”. You can sign up for free email table of contents alerts.

The first paper, ‘The masked sample covariance estimator: an analysis using matrix concentration inequalities‘, has been made available for advanced online access.

**More information**: Oxford Journals: *Information and Inference: a Journal of the IMA**.*