Corey Chivers on P(A|B) ∝P(B|A)P(A)
Recently at home with my mom and sister and I was explaining a bit about the work I m going to be doing in AI for digital pathology. We got talking about how there is so much data, but a scarcity of good labels, what self-supervised learning is and how it can help overcome this. As [ ]
In Magritte s famous 1929 painting The Treachery of Images, a pipe is depicted with the caption Ceci n est pas une pipe , French for This is not a pipe . The seemingly dissonant statement under what is a very clearly depicted pipe forces the viewer to confront the distinction between the representation and the thing itself. The [ ]
I was intrigued by the recent splashy result showing how eigenvectors can be computed from eigenvalues alone. The finding was covered in Quanta magazine and the original paper is pretty easy to understand, even for a non-mathematician. Being a non-mathematician myself, I tend to look for insights and understanding via computation, rather than strict proofs. [ ]
I was recently fortunate to be invited to speak with an impressive group of high-school students as a part of the Germination Project. They came to Penn to learn about innovation in health care and I spoke with them about how we re using Data Science to improve patient outcomes.
The theme for this year s workshop will be Moving beyond supervised learning in healthcare . This will be a great forum for those who work on computational solutions to the challenges facing clinical medicine. The submission deadline is Friday Oct 26, 2018. Hope to see you there! https://ml4health.github.io/2018/pages/call-for-papers.html
This week I spoke at DataJawn, an super fun evening of talks and mingling with Philly s data nerds. You can have a look through the slides here.
Some (opinionated) themes and highlights from this year s NIPS conference:
Lately I ve been thinking a lot about the connection between prediction models and the decisions that they influence. There is a lot of theory around this, but communicating how the various pieces all fit together with the folks who will use and be impacted by these decisions can be challenging. One of the important conceptual pieces [ ]
Happy Halloween! Code.
If you build and/or use classifiers in your life, feel free to print this out and keep it above you desk.