ML4H registration is open & FREE! See the link below. I'm particularly excited about the new research roundtables & career mentorship- these are our attempt to make the virtual format more engaging by having small group discussions in gather.town See you on Dec 4th!

Today, raia hadsell, Kyunghyun Cho and I are happy to announce the creation of a new journal: Transaction on Machine Learning Research (TMLR) Learn more in our post: medium.com/@hugo_larochel…

This is my *top 10* favorite methods papers of 2021

#2: This short correspondence gives a nice overview of ways to recognize and mitigate a phenomenon known as dataset shift Access (paywall) 👉 nejm.org/doi/10.1056/NE… Key table of the article freely available 👉 sgfin.github.io/assets/dataset…

Check out the beginning of a series of posts on external validity. Excited to read the next ones. See also some response threads from coauthors and me: x.com/_asubbaswamy/s… x.com/kdpsinghlab/st… x.com/IAmSamFin/stat…

Announcing the ICML Workshop on Principles of Distribution Shift (PODS)! Submit your 4-pagers on theoretical foundations, real applications, benchmarks (or the validity thereof), & position pieces. Also, the speaker list slaps. Site: sites.google.com/view/icml-2022… Deadline: May 22

7th ML4H will take place November 28 in New Orleans + virtual, collocated with NeurIPS submit your work by September 1 CfP: ml4health.github.io/2022/call_for_… full paper proceedings in PMLR (last year's proceedings.mlr.press/v158/ ) + extended abstract track Hope to see many irl in November

If you’re at #ICML2023 join me here: sites.google.com/view/scis-work… Giving an invited talk later today on AI Safety. Below are some of the papers our lab has written on the topic in last 5 yrs; this talk will give a brief overview and focus on learning/evaluation.

Our #UAI2023 paper is on detecting novel subgroups (aka classes/categories) when distribution of non-novel data shifts. If this sounds interesting, or you’re wondering what it has to do with unicorns, check out our poster/paper/drop a line. w/ Suchi Saria proceedings.mlr.press/v216/wald23a.h…

How do people manage to keep track of ML papers? This is not a request for support in my current state of bewilderment - I'm genuinely asking what strategies seem to work to read (or "read") what appear to be 100s of papers per day.

I'm talking at today's NeurIPS #RegulatableML workshop about why designing monitoring systems for ML-based medical devices is complicated, why we need a systematic framework for comparing all the different monitoring strategies, and our first steps to developing such a framework.

Our framework brings together ideas from causal inference and statistical process control. Please drop by if you're interested! Preprint here: arxiv.org/abs/2311.11463 It was wonderful working on this with coauthors from UCSF and FDA! Romain Pirracchio Adarsh Subbaswamy Harvineet Singh

It turns out monitoring the performance of ML models is hard, especially in settings like healthcare where model predictions affect user decisions If you're at NeurIPS check out Jean's talk and we'd love to hear your thoughts re monitoring

What if a platform existed to help doctors make faster more accurate diagnoses? INDEX intends to create a high-quality medical imaging platform that does not currently exist to benefit the entire imaging ecosystem. arpa-h.gov/news-and-event…