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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.
Optimally Deceiving a Learning Leader in Stackelberg Games
For this strategic behavior to be successful, the main challenge faced by the follower is to pinpoint the payoffs that would make the learning algorithm compute a commitment so that best responding to it maximizes the follower's utility, according to his true payoffs.
On learning k-parities with and without noise
We improve the previous best result of Buhrman et al. by an $\exp(k)$ factor in the time complexity.
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