zlacker

Is a preprint of your paper available?

I looked at your blog a bit and was able to find this, which may be it?

> Learning Interpretable Models Using Uncertainty Oracles

https://arxiv.org/abs/1906.06852

https://doi.org/10.48550/arXiv.1906.06852

>>aspenm+(OP)
Yes, that's the one: https://arxiv.org/pdf/1906.06852

>>abhgh+u
I copied the DOI for convenience but they’re the same paper.

I have no formal math background really so I can’t speak to your methods but I appreciate that you have shared your work freely.

Did you have any issues defending your thesis due to the issues you described above related to publishing?

Noticed a typo in your abstract:

“Maybe” should be “may be” in sentence below (italics):

> We show that this technique addresses the above challenges: (a) it arrests the reduction in accuracy that comes from shrinking a model (in some cases we observe ~ 100% improvement over baselines), and also, (b) that this maybe applied with no change across model families with different notions of size; results are shown for Decision Trees, Linear Probability models and Gradient Boosted Models.

>>aspenm+L
Yes, it did come up during my defense, but it was deemed not to be a concern since I had one prior paper [1] (the original one in this thread of work, the paper I linked above was an improvement over it), and my advisor (co-author on both papers) vouched for the quality of the work.

Thank you for pointing out the typo - will fix it!

[1] https://www.frontiersin.org/journals/artificial-intelligence...