I have the chance to present my work at the Google Ph.D. Intern Research Conference (PIRC). This poster represents all of the work we have added to the Moliere project since our original paper last year.
Today in a class, we were asked to write an iterative solver for numerical equations. Now, many students in the class did not have an optimization background, so for the benefit of everyone, I want to share a simple overview of this exercise and how to go about solving it.
The problem was stated as follows:
$$ M(a) = 2\times a + 14$$ $$ G(b) = b - 2 $$
And our goal was to find some solution $x$ such that $M(x) = G(x)$. Additionally, we were supposed to do so iteratively, so just solving the system of equations was out of the question. This is because our next exercise would have a different $M$ and $G$, so our code should be able to support whatever.
For the sake of generalization, my solution here will assume only the $M$ and $G$ are continuous, but I will not assume we know their derivatives. Additionally, I will be writing my code in python, simply because I find that it is easier for anybody to understand. Knowledge of python, hopefully, won’t be necessary. But first, lets go over some aspects of the problem…
Over the last couple of days, I have retooled MOLIERE into a system that anyone1 can deploy it and run their own queries.
The code is over at the default repo2 and should be pretty straightforward, the code even downloads raw data itself!
build_network.py and point it at a big parallel file systen — in a few hours you’ll have your very own knowledge network!
We have publicly available code and experimental data. Our validation information has been incorporated to THIS REPO.
Our experimental data and results can be found in THIS OTHER REPO.
But, we are still working on uploading all of the supporting data.
I have finally had time to package Moliere, our Automatic Hypothesis Generation System, into a single easy-to-use package!
Take a second to check it out at my repo.