1. Two Sides of the Coin Problem Gil Cohen Joint with: Anat Ganor and Ran Raz

2. The Coin Problem

3. 1 0 0 1 1 0 1 Promise Majority [Ajtai83, AjtaiBenOr84, Stockmeyer85, Ajtai93, Amano09, Viola09, Viola11, KoppartySrinivasan12, CDIKMRR13]

4. The Coin Problem 0 1 1 1 0 0 1 0 0 1 1 0 1 Promise Majority [O’DonnellWimmer07, Amano09] Approximating Majority

5. The Coin Problem 0 1 1 1 0 0 1 0 0 1 1 0 1 1 0 0 1 1 0 1 0 1 Promise Majority [ShaltielViola08, Aaronson10, BrodyVerbin10, Steinberger13] Approximating Majority The Coin Problem

6. Read Once Branching Programs Outperforms the naïve “take the last sample” algorithm.

7. It is All About the Bias Theorem 1 (informal). It is all about the bias - ROBPs cannot make use of the dependencies.

8. It is All About the Bias Proof Idea. Black-box reduction to the coin problem.

9. AC Circuits 0 Motivation came from hardness amplification and oracle separation between BQP and PH, respectively.

10. Random Restrictions Majority Or =

11. Distinguishability and Random Restrictions Definition. When.

12. Summary and Open Problems * For ROBPs it is all about the bias. Thank you for your attention! * Any application of the SV result for PRGs?