Podcasts about rigollet

Guests: Jesjit Gil, Moritz Grünke, and Mari Campistron Host: Christopher Kardambikis Recorded November 18th at Magical Riso held at the Jan Van Eyck Academie in Maastricht, Netherlands. Jesjit Gil is the co-founder of Colour Code, established in 2012. Colour Code is an independent print studio and publishing platform based in Toronto, Canada. They specialize in high quality, artist friendly printing for local, US and international customers. Colour Code also publishes and distributes small-run artist books, comics, posters and other printed matter. Moritz Grünke is the co-founder of We make it, a Risograph printing and design studio, a library and exhibition space based in Berlin dedicated to artists, designers and people who love excellent and handcrafted printed matter. We make it is a project by Franziska Brandt und Moritz Grünke who also founded Gloria Glitzer, a small press for artists books, in 2007. Since then they published lots of artzines, attends at many art(ists’) book fairs all over Europe and curated several exhibitions on self-publishing artists. Moritz Grünke also collects artists’ publications and founded artzines.de a blog dedicated to self-publishing artists in 2010. MARI CAMPISTRON is a Glasgow based illustrator who currently works as a print technician and studio manager at RISOTTO studio. She is part of the collective Riso Sur Mer along with Élise Rigollet, Inès Gradot, Joséphine Ohl and Margaux Bigou. Between Paris and Glasgow, they collaborate on various projects from zines to posters, calendars or books, all based around the Risograph print technique. Find out more about Mari here. --- Support this podcast: https://anchor.fm/paper-cuts/support

In this lecture, Prof. Rigollet talked about Hessian, Fisher information, weighted least squares, and iteratively reweighed least squares.

In this lecture, Prof. Rigollet talked about strict concavity, optimization methods, quadratic approximation, Newton-Raphson method, and Fisher-scoring method.

In this lecture, Prof. Rigollet talked about log-likelihood function, link function, and canonical link, etc.

In this lecture, Prof. Rigollet talked about linear model, generalization, and examples of disease occurring rate, prey capture rate, Kyphosis data, etc.

In this lecture, Prof. Rigollet talked about principal component analysis: main principle, algorithm, example, and beyond practice.

In this lecture, Prof. Rigollet reviewed linear algebra and talked about multivariate statistics.

In this lecture, Prof. Rigollet talked about Bayesian confidence regions and Bayesian estimation.

In this lecture, Prof. Rigollet talked about Bayesian approach, Bayes rule, posterior distribution, and non-informative priors.

In this lecture, Prof. Rigollet talked about significance test and other tests.

In this lecture, Prof. Rigollet talked about linear regression with deterministic design and Gaussian noise.

In this lecture, Prof. Rigollet talked about linear regression and multivariate case.

In this lecture, Prof. Rigollet talked about Kolmogorov-Lilliefors test, Quantile-Quantile plots, and Kai-squared goodness-of-fit test.

In this lecture, Prof. Rigollet talked about Glivenko-Cantelli Theorem (fundamental theorem of statistics), Donsker’s Theorem, and Kolmogorov-Smirnov test.

In this lecture, Prof. Rigollet talked about Wald's test, likelihood ratio test, and testing implicit hypotheses.

In this lecture, Prof. Rigollet talked about statistical formulation, Neyman-Pearson’s paradigm, and Kai-squared distribution.

In this lecture, Prof. Rigollet talked about parametric hypothesis testing and discussed Cherry Blossom run and clinical trials as examples.

In this lecture, Prof. Rigollet continued on maximum likelihood estimators and talked about Weierstrass Approximation Theorem (WAT), and statistical application of the WAT, etc.

In this lecture, Prof. Rigollet talked about maximizing/minimizing functions, likelihood, discrete cases, continuous cases, and maximum likelihood estimators.

In this lecture, Prof. Rigollet talked about confidence intervals, total variation distance, and Kullback-Leibler divergence.

In this lecture, Prof. Rigollet talked about statistical modeling and the rationale behind statistical modeling.

In this lecture, Prof. Rigollet talked about the importance of the mathematical theory behind statistical methods and built a mathematical model to understand the accuracy of the statistical procedure.