Macro Scale Agent Based Modeling

I was reading about this book called Factfulness: Ten Reasons We’re Wrong About the World—and Why Things Are Better Than You Think by Hans Rosling that Bill Gates recommend reading. From this I found the Gapminder (which is a spin off from Han’s work) and their tool: https://www.gapminder.org/tools/#$chart-type=bubbles which lets you explore a dizzying number of statistics… Continue reading Macro Scale Agent Based Modeling

Jupyter notebooks

Some interesting projects: Google has there own modified jupyter notebook that integrates into google drive: https://colab.research.google.com/ And there is Binder (beta) that will create an executable jupyter environment from a github repo with jupyter notebooks.  Then anyone can easily run your code. https://mybinder.org/

Adaptive Data Analysis

Google Research recently wrote a piece The reusable holdout: Preserving validity in adaptive data analysis  (so I’m not go to write much).  It details the problem with statistics generated when the machine learning methods are adapted to the data through data analysis and repeated trials on the same hold out data.  This is a problem that is… Continue reading Adaptive Data Analysis

Fun problem

David had an idea for a problem: Given N individuals, each individual must, say, play a game with M other individuals.  The length of the game is stochastic and dependent on who is playing the game.  Describe an algorithm that will optimally group the individuals such that each individual has to wait the minimum amount… Continue reading Fun problem

Automatic feature selection for Horde

I think that fractal clustering could be used to cluster data streams of electricity data. What about distributed clustering algorithms?  So, we have massive data streams from different parts of the grid coming in to their respective hubs.  How do you make sense of the whole?  I think fractal clustering would work here.  I believe… Continue reading Automatic feature selection for Horde