Explicit Resilient Functions Matching Ajtai-Linial

A Boolean function on n variables is q-resilient if for any subset of at most q variables, the function is very likely to be determined by a uniformly random assignment to the remaining n-q variables; in other words, no coalition of at most q variables has significant influence on the function. Resilient functions have been extensively studied with a variety of applications in cryptography, distributed computing, and pseudorandomness. The best known balanced resilient function on n variables due to Ajtai and Linial ([AL93]) is Omega(n/(log^2 n))-resilient. However, the construction of Ajtai and Linial is by the probabilistic method and does not give an efficiently computable function. In this work we give an explicit monotone depth three almost-balanced Boolean function on n bits that is Omega(n/(log^2 n))-resilient matching the work of Ajtai and Linial. The best previous explicit construction due to Meka [Meka09] (which only gives a logarithmic depth function) and Chattopadhyay and Zuckermman [CZ15] were only n^{1-c}-resilient for any constant c < 1. Our construction and analysis are motivated by (and simplifies parts of) the recent breakthrough of [CZ15] giving explicit two-sources extractors for polylogarithmic min-entropy; a key ingredient in their result was the construction of explicit constant-depth resilient functions. An important ingredient in our construction is a new randomness optimal oblivious sampler which preserves moment generating functions of sums of variables and could be useful elsewhere.

[1]  Gil Cohen,et al.  Two-source dispersers for polylogarithmic entropy and improved ramsey graphs , 2015, Electron. Colloquium Comput. Complex..

[2]  Noam Nisan,et al.  Pseudorandomness for network algorithms , 1994, STOC '94.

[3]  Noga Alon,et al.  The Probabilistic Method , 2015, Fundamentals of Ramsey Theory.

[4]  Ravi B. Boppana,et al.  Perfect-Information Leader Election with Optimal Resilience , 2000, SIAM J. Comput..

[5]  Xin Li,et al.  Three-Source Extractors for Polylogarithmic Min-Entropy , 2015, 2015 IEEE 56th Annual Symposium on Foundations of Computer Science.

[6]  Andrew Wan,et al.  Mansour's Conjecture is True for Random DNF Formulas , 2010, COLT.

[7]  Alexander Healy,et al.  Randomness-Efficient Sampling within NC1 , 2006, computational complexity.

[8]  Michael E. Saks,et al.  Lower bounds for leader election and collective coin-flipping in the perfect information model , 1999, STOC '99.

[9]  Madhur Tulsiani,et al.  Improved Pseudorandom Generators for Depth 2 Circuits , 2010, APPROX-RANDOM.

[10]  Noam Nisan,et al.  Constant depth circuits, Fourier transform, and learnability , 1993, JACM.

[11]  Nathan Linial,et al.  Collective coin flipping, robust voting schemes and minima of Banzhaf values , 1985, 26th Annual Symposium on Foundations of Computer Science (sfcs 1985).

[12]  Mark Braverman Poly-logarithmic Independence Fools AC0 Circuits , 2009, Computational Complexity Conference.

[13]  Nathan Linial,et al.  The influence of large coalitions , 1993, Comb..

[14]  Nabil Kahale Large Deviation Bounds for Markov Chains , 1997, Comb. Probab. Comput..

[15]  Uriel Feige,et al.  Noncryptographic selection protocols , 1999, 40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039).

[16]  Mark Braverman,et al.  Poly-logarithmic Independence Fools AC^0 Circuits , 2009, 2009 24th Annual IEEE Conference on Computational Complexity.

[17]  Nathan Linial,et al.  The Influence of Variables on Boolean Functions (Extended Abstract) , 1988, FOCS 1988.

[18]  Noam Nisan,et al.  Pseudorandom generators for space-bounded computation , 1992, Comb..

[19]  David Zuckerman,et al.  Explicit two-source extractors and resilient functions , 2016, Electron. Colloquium Comput. Complex..

[20]  J. Bourgain,et al.  MORE ON THE SUM-PRODUCT PHENOMENON IN PRIME FIELDS AND ITS APPLICATIONS , 2005 .

[21]  A. Razborov Lower bounds on the size of bounded depth circuits over a complete basis with logical addition , 1987 .

[22]  Daniel M. Kane,et al.  Pseudorandomness via the Discrete Fourier Transform , 2015, 2015 IEEE 56th Annual Symposium on Foundations of Computer Science.

[23]  Alexander Russell,et al.  Perfect Information Leader Election in log* n+O (1) Rounds , 2001, J. Comput. Syst. Sci..

[24]  Ding‐Zhu Du,et al.  Wiley Series in Discrete Mathematics and Optimization , 2014 .

[25]  Avi Wigderson,et al.  2-source dispersers for $n^{o(1)}$ entropy, and Ramsey graphs beating the Frankl-Wilson construction , 2012 .

[26]  Noga Alon,et al.  Coin-Flipping Games Immune Against Linear-Sized Coalitions , 1993, SIAM J. Comput..

[27]  David Zuckerman Randomness-optimal oblivious sampling , 1997, Random Struct. Algorithms.

[28]  Roman Smolensky,et al.  Algebraic methods in the theory of lower bounds for Boolean circuit complexity , 1987, STOC.

[29]  Noam Nisan,et al.  Randomness is Linear in Space , 1996, J. Comput. Syst. Sci..

[30]  Michael E. Saks A Robust Noncryptographic Protocol for Collective Coin Flipping , 1989, SIAM J. Discret. Math..