What I learned this week: 16/2015

Statistics, Probability, Machine Learning, Data Science

1. Multiple comparisons

Finally had a look into multiple comparisons beyond Bonferroni’s correction. Didn’t yet get around to read Gelman’s Why We (Usually) Don’t Have to Worry About Multiple Comparisons (pdf).

2. Robust regression, Quantile Regression

Do you know Warren Buffet’s adage “You get, what you incentivize for”? Well, in machine learning:

You get what you optimize for.

After weeks of arguing for MAE instead of RMSE for model evaluation in a project, I finally had to eat my own dog food: not only to evaluate a model on MAE, but actually optimize for it. This opened a new world for me with Robust versions of regression (Huber loss functions) and quantile regression.

There is a ton to learn here, looking forward to it.

3. Sorting through my thoughts on Knightian uncertainty

Here. Still some work left to do on extensions of expectation maximization.

General Stuff

Kerfuffle around Growth mindset

The Shortest-Known Paper Published in a Serious Math Journal

Anti-market opportunities

  • Good formulation – something to live by, if I ever return to academia.


  • Oh, the sweet, sweet naivety. I’d enjoy working like this, but one should read up on suboptimisation.

The button

Productivity, Life Advice

Summary of Ikigai by Sebastian Marshall 1

Summary of Ikigai by Sebartian Marshall 2

  • Not sure if I’ll read the book, but the summaries have good formulations of some well known thoughts.

What You’ll Wish You’d Known by Paul Graham 

  • Indeed.

How to Stick With Good Habits Every Day by Using the “Paper Clip Strategy”

  • Habbit building strategies are dime a dozen, but this one I haven’t heard before. It sounds cute and I can absolutely imagine it works for ugh-mine-fields.


Evaluating Trading Strategies

  • Pretty good overview of the multiple comparison corrections

Videos / Lectures

Randy Pausch Last Lecture: Achieving Your Childhood Dreams

  • No, I just got some mote in my eye.

Conversations with Tyler: Peter Thiel on the Future of Innovation

  • Cowen did a good job with the questions and steering the conversation. Highly recommended.

Books: Non-Fiction

The Undercover Economist Strikes Back: How to Run–or Ruin–an Economy

Books: Fiction

Schild’s Ladder: A Novel


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