Ben Moseley
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| title | conference | date |
|---|---|---|
| Machine Learning for Faster Optimization | Quantifying Uncertainty: Stochastic, Adversarial, and Beyond | 2022-09-12 |
A model augments classical algorithms with predicted parameters that are provably learnable from past instances and robust to modest input changes. Examples… | ||
| Pragmatism, Puritanism and Functional Programming | Tech Mesh 2012 | 2012-12-04 |
Argues that using Haskell and GHC in an industrial codebase of hundreds of thousands of lines yields measurably simpler, more readable programs: purity plus a… | ||
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