#appliedml — Public Fediverse posts

Swiss AI Days 2026 Peer-Reviewed Papers Track Submissions are Open!

And as the publication chair this year, I am really excited about it.

https://ai-days.swiss-ai-center.ch/en/call-for-contributions/papers

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#AI #ML #AppliedML #Conferences

Mind the predict/fit switcheroo #appliedml #onlinelearning https://maxhalford.github.io/blog/predict-fit-switcheroo/

Anyway, I keep meaning to write up a blog post on “falsehoods I have believed about measuring model performance” touching on #AppliedML issues related to #modelEvaluation, #metrics, #monitoring, #observability, and #experiments (#RCTs). The cool kids would call this #AIAlignment in their VC pitch decks, but even us #NormCore ML engineers have to wrestle with how to measure and optimize the real-world impact of our models.

You have a problem: you currently pick thresholds for model-based actions using some arbitrary heuristic.

Your solution: pick the threshold that maximizes expected utility (e.g. revenue, profit, ROI, …) instead. That’s the definition of the rational decision, right?

Hmm, for some reason you now seem to have several more problems.
#DecisionTheory #Optimization #rationality #AppliedML

You have a problem: you currently pick thresholds for model-based actions using some arbitrary heuristic.

Your solution: pick the threshold that maximizes expected utility (e.g. revenue, profit, ROI, …) instead. That’s the definition of the rational decision, right?

Hmm, for some reason you now seem to have several more problems.
#DecisionTheory #Optimization #rationality #AppliedML

You have a problem: you currently pick thresholds for model-based actions using some arbitrary heuristic.

Your solution: pick the threshold that maximizes expected utility (e.g. revenue, profit, ROI, …) instead. That’s the definition of the rational decision, right?

Hmm, for some reason you now seem to have several more problems.
#DecisionTheory #Optimization #rationality #AppliedML

You have a problem: you currently pick thresholds for model-based actions using some arbitrary heuristic.

Your solution: pick the threshold that maximizes expected utility (e.g. revenue, profit, ROI, …) instead. That’s the definition of the rational decision, right?

Hmm, for some reason you now seem to have several more problems.
#DecisionTheory #Optimization #rationality #AppliedML

You have a problem: you currently pick thresholds for model-based actions using some arbitrary heuristic.

Your solution: pick the threshold that maximizes expected utility (e.g. revenue, profit, ROI, …) instead. That’s the definition of the rational decision, right?

Hmm, for some reason you now seem to have several more problems.
#DecisionTheory #Optimization #rationality #AppliedML

Uncertainty about the inner workings of #machinelearning models holds back the application of ML-enabled systems in real estate markets. How do ML models arrive at their estimates?
How can practitioners guarantee that ML systems do not run afoul of the law?

Wayne Wan and I show how ML systems can be externally tested with dedicated system tests (as commonly done in software development).

#newpaperalert #appliedML #realestate #proptech #explainableML

https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6229.12416