Extractors from Reed-Muller Codes

Finding explicit extractors is an important derandomization goal that has received a lot of attention in the past decade. Previous research has focused on two approaches, one related to hashing and the other to pseudorandom generators. A third view, regarding extractors as good error correcting codes, was noticed before. Yet, researchers had failed to build extractors directly from a good code without using other tools from pseudorandomness. We succeed in constructing an extractor directly from a Reed-Muller code. To do this, we develop a novel proof technique.Furthermore, our construction is the first to achieve degree close to linear. In contrast, the best previous constructions brought the log of the degree within a constant of optimal, which gives polynomial degree. This improvement is important for certain applications. For example, it was used [E. Mossel, C. Umans, On the complexity of approximating the VC dimension, J. Comput. System Sci. 65 (2002) 660-671] to show that approximating VC dimension to within a factor of N1-δ is AM-hard for any positive δ.

[1]  Miklos Santha,et al.  Generating Quasi-random Sequences from Semi-random Sources , 1986, J. Comput. Syst. Sci..

[2]  Avi Wigderson,et al.  Extracting randomness via repeated condensing , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[3]  Carsten Lund,et al.  On the hardness of approximating minimization problems , 1994, JACM.

[4]  C. Umans Hardness of Approximating Minimization Problems , 1999, FOCS 1999.

[5]  Oded Goldreich,et al.  Unbiased Bits from Sources of Weak Randomness and Probabilistic Communication Complexity , 1988, SIAM J. Comput..

[6]  Ran Raz,et al.  Extracting all the randomness and reducing the error in Trevisan's extractors , 1999, STOC '99.

[7]  Luca Trevisan,et al.  Pseudorandom generators without the XOR Lemma (extended abstract) , 1999, STOC '99.

[8]  Christopher Umans Pseudo-random generators for all hardnesses , 2002, STOC '02.

[9]  Michael Sipser,et al.  Expanders, Randomness, or Time versus Space , 1988, J. Comput. Syst. Sci..

[10]  Noam Nisan,et al.  Hardness vs Randomness , 1994, J. Comput. Syst. Sci..

[11]  Luca Trevisan,et al.  Extractors and pseudorandom generators , 2001, JACM.

[12]  J. Håstad Clique is hard to approximate withinn1−ε , 1999 .

[13]  Luca Trevisan,et al.  Pseudorandom generators without the XOR lemma , 1999, Proceedings. Fourteenth Annual IEEE Conference on Computational Complexity (Formerly: Structure in Complexity Theory Conference) (Cat.No.99CB36317).

[14]  Amnon Ta-Shma,et al.  On Extracting Randomness From Weak Random Sources , 1995, Electron. Colloquium Comput. Complex..

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

[16]  Avi Wigderson,et al.  Extractors and pseudo-random generators with optimal seed length , 2000, STOC '00.

[17]  Miklos Santha,et al.  On Using Deterministic Functions to Reduce Randomness in Probabilistic Algorithms , 1987, Inf. Comput..

[18]  Elchanan Mossel,et al.  On the complexity of approximating the VC dimension , 2001, Proceedings 16th Annual IEEE Conference on Computational Complexity.

[19]  Amnon Ta-Shma,et al.  On extracting randomness from weak random sources (extended abstract) , 1996, STOC '96.

[20]  J. Håstad Clique is hard to approximate within n 1-C , 1996 .

[21]  Madhu Sudan,et al.  Decoding of Reed Solomon Codes beyond the Error-Correction Bound , 1997, J. Complex..

[22]  Oded Goldreich,et al.  Another proof that bpp?ph (and more) , 1997 .

[23]  Lars Engebretsen,et al.  Clique Is Hard To Approximate Within , 2000 .

[24]  Avi Wigderson,et al.  Near-optimal conversion of hardness into pseudo-randomness , 1999, 40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039).

[25]  Avi Wigderson,et al.  Expanders That Beat the Eigenvalue Bound: Explicit Construction and Applications , 1993, Comb..

[26]  Jaikumar Radhakrishnan,et al.  Bounds for Dispersers, Extractors, and Depth-Two Superconcentrators , 2000, SIAM J. Discret. Math..

[27]  C. Umans Hardness of Approximating p 2 Minimization Problems , 1999 .

[28]  Luca Trevisan,et al.  Construction of extractors using pseudo-random generators (extended abstract) , 1999, STOC '99.

[29]  Amnon Ta-Shma,et al.  Loss-less condensers, unbalanced expanders, and extractors , 2001, STOC '01.

[30]  Venkatesan Guruswami,et al.  Combinatorial bounds for list decoding , 2002, IEEE Trans. Inf. Theory.

[31]  Moni Naor,et al.  Small-Bias Probability Spaces: Efficient Constructions and Applications , 1993, SIAM J. Comput..

[32]  Aravind Srinivasan,et al.  Computing with very weak random sources , 1994, Proceedings 35th Annual Symposium on Foundations of Computer Science.

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

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

[35]  Christopher Umans,et al.  Simple extractors for all min-entropies and a new pseudo-random generator , 2001, Proceedings 2001 IEEE International Conference on Cluster Computing.

[36]  David Zuckerman,et al.  General weak random sources , 1990, Proceedings [1990] 31st Annual Symposium on Foundations of Computer Science.

[37]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.