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On the Power of Interactive Proofs for Learning
- We construct an interactive protocol for learning the $t$ largest Fourier characters of a given function $f \colon \{0, 1\}^n \to \{0, 1\}$ up to an arbitrarily small error, wherein the verifier uses $\mathsf{poly}(t)$ random examples.
Private Boosted Decision Trees via Smooth Re-Weighting
Differential Privacy is the appropriate mathematical framework for formal guarantees of privacy, and boosted decision trees are a popular machine learning technique.
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