Private Multi-Party Machine Learning

The one-day workshop focuses on the problem of privacy-preserving machine learning in scenarios where sensitive datasets are distributed across multiple data owners. Such distributed scenarios occur quite often in practice, for example when different part…

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Machine Learning in Haskell

Much advocacy of Haskell, in general, boils down to type-safety and elimination of bugs. How boring. My personal experience is that bugs are trickier in Haskell and I can write bad code in an extraordinary variety of ways. I don’t code in Haskell to help ... (more…)

Read more »

Machine Learning in Haskell

Much advocacy of Haskell, in general, boils down to type-safety and elimination of bugs. How boring. My personal experience is that bugs are trickier in Haskell and I can write bad code in an extraordinary variety of ways. I don’t code in Haskell to help ... (more…)

Read more »