dev | ml | math

01 Jun 2020

A Broader Emergence (Simpson’s part 3 of 3) One neat takeaway from the previous post was really around the structure...

01 May 2020

An Infinite Simpsons Paradox (Simpson’s part 2 of 3) This is Problem 9.11 in Elements of Causal Inference. Construct a...

01 Apr 2020

Observational Causal Inference (Simpson’s part 1 of 3) In most data analysis, especially in business contexts, we’re looking for answers...

07 Mar 2020

Subset Isomorphism Much of scientific computing revolves around the manipulation of indices. Most formulas involve sums of things and at...

22 Feb 2020

Graph Coloring for Machine Learning This month, I posted a blog entry on Sisu’s engineering blog post. I discuss an...

05 Jan 2020

Stop Anytime Multiplicative Weights Multiplicative weights is a simple, randomized algorithm for picking an option among \(n\) choices against an...

01 Dec 2019

Metaphysics of Causality If you read Judea Pearl’s The Book of Why, it makes it seem like exercising observational statistics...

30 Nov 2019

The Triple Staple When reading, I prefer paper to electronic media. Unfortunately, a lot of my reading involves manuscripts from...

20 Oct 2019

PRNGs Trying out something new here with a Jupyter notebook blog post. We’ll keep this short. Let’s see how it...

11 Sep 2019

Compressed Sensing and Subgaussians Candes and Tao came up with a broad characterization of compressed sensing solutions a while ago....

18 Aug 2019

Making Lavender I’ve tried using Personal Capital and Mint to monitor my spending, but I wasn’t happy with what those...

18 Jul 2019

FAISS, Part 1 FAISS is a powerful GPU-accelerated library for similarity search. It’s available under MIT on GitHub. Even though...

18 Jul 2019

FAISS, Part 2 I’ve previously motivated why nearest-neighbor search is important. Now we’ll look at how FAISS solves this problem....

23 Jun 2019

BERT In the last two posts, we reviewed Deep Learning and The Transformer. Now we can discuss an interesting advance...

22 Jun 2019

BERT Prerequisite 2: The Transformer In the last post, we took a look at deep learning from a very high...

09 Mar 2019

A Modeling Introduction to Deep Learning In this post, I’d like to introduce you to some basic concepts of deep...

19 Jan 2019

Numpy Gems 1: Approximate Dictionary Encoding and Fast Python Mapping Welcome to the first installment of Numpy Gems, a deep...

22 Dec 2018

Subgaussian Concentration This is a quick write-up of a brief conversation I had with Nilesh Tripuraneni and Aditya Guntuboyina a...

23 Dec 2017

Beating TensorFlow Training in-VRAM In this post, I’d like to introduce a technique that I’ve found helps accelerate mini-batch SGD...

09 Jul 2017

Deep Learning Learning Plan This is my plan to on-board myself with recent deep learning practice (as of the publishing...