TY - GEN
T1 - Simple and efficient pseudorandom generators from Gaussian processes
AU - Chattopadhyay, Eshan
AU - De, Anindya
AU - Servedio, Rocco A.
N1 - Funding Information:
Funding Eshan Chattopadhyay: Supported by NSF grants CCF-1412958, CCF-1849899, and the Simons foundation. Part of the work done while the author was a postdoctoral researcher at the Institute for Advanced Study, Princeton.
Funding Information:
Eshan Chattopadhyay: Supported by NSF grants CCF-1412958, CCF-1849899, and the Simons foundation. Part of the work done while the author was a postdoctoral researcher at the Institute for Advanced Study, Princeton.
Funding Information:
Anindya De: Supported by NSF CCF 1926872 (transferred from CCF 1814706). Work done while the author was at Northwestern University supported by a start-up grant. Rocco A. Servedio: Supported by NSF CCF 1814873, NSF CCF 1563155, and by the Simons Collaboration on Algorithms and Geometry.
Publisher Copyright:
© Eshan Chattopadhyay, Anindya De, and Rocco A. Servedio; licensed under Creative Commons License CC-BY 34th Computational Complexity Conference (CCC 2019).
PY - 2019/7/1
Y1 - 2019/7/1
N2 - We show that a very simple pseudorandom generator fools intersections of k linear threshold functions (LTFs) and arbitrary functions of k LTFs over n-dimensional Gaussian space. The two analyses of our PRG (for intersections versus arbitrary functions of LTFs) are quite different from each other and from previous analyses of PRGs for functions of halfspaces. Our analysis for arbitrary functions of LTFs establishes bounds on the Wasserstein distance between Gaussian random vectors with similar covariance matrices, and combines these bounds with a conversion from Wasserstein distance to “union-of-orthants” distance from [5]. Our analysis for intersections of LTFs uses extensions of the classical Sudakov-Fernique type inequalities, which give bounds on the difference between the expectations of the maxima of two Gaussian random vectors with similar covariance matrices. For all values of k, our generator has seed length O(log n) + poly(k) for arbitrary functions of k LTFs and O(log n) + poly(log k) for intersections of k LTFs. The best previous result, due to [14], only gave such PRGs for arbitrary functions of k LTFs when k = O(log log n) and for intersections of k LTFs when k = O(logloglognn). Thus our PRG achieves an O(log n) seed length for values of k that are exponentially larger than previous work could achieve. By combining our PRG over Gaussian space with an invariance principle for arbitrary functions of LTFs and with a regularity lemma, we obtain a deterministic algorithm that approximately counts satisfying assignments of arbitrary functions of k general LTFs over {0, 1}n in time poly(n)·2poly(k,1/ε) for all values of k. This algorithm has a poly(n) runtime for k = (log n)c for some absolute constant c > 0, while the previous best poly(n)-time algorithms could only handle k = O(log log n). For intersections of LTFs, by combining these tools with a recent PRG due to [28], we obtain a deterministic algorithm that can approximately count satisfying assignments of intersections of k general LTFs over {0, 1}n in time poly(n) · 2poly(log k,1/ε). This algorithm has a poly(n) runtime for k = 2(log n)c for some absolute constant c > 0, while the previous best poly(n)-time algorithms for intersections of k LTFs, due to [14], could only handle k = O(logloglognn).
AB - We show that a very simple pseudorandom generator fools intersections of k linear threshold functions (LTFs) and arbitrary functions of k LTFs over n-dimensional Gaussian space. The two analyses of our PRG (for intersections versus arbitrary functions of LTFs) are quite different from each other and from previous analyses of PRGs for functions of halfspaces. Our analysis for arbitrary functions of LTFs establishes bounds on the Wasserstein distance between Gaussian random vectors with similar covariance matrices, and combines these bounds with a conversion from Wasserstein distance to “union-of-orthants” distance from [5]. Our analysis for intersections of LTFs uses extensions of the classical Sudakov-Fernique type inequalities, which give bounds on the difference between the expectations of the maxima of two Gaussian random vectors with similar covariance matrices. For all values of k, our generator has seed length O(log n) + poly(k) for arbitrary functions of k LTFs and O(log n) + poly(log k) for intersections of k LTFs. The best previous result, due to [14], only gave such PRGs for arbitrary functions of k LTFs when k = O(log log n) and for intersections of k LTFs when k = O(logloglognn). Thus our PRG achieves an O(log n) seed length for values of k that are exponentially larger than previous work could achieve. By combining our PRG over Gaussian space with an invariance principle for arbitrary functions of LTFs and with a regularity lemma, we obtain a deterministic algorithm that approximately counts satisfying assignments of arbitrary functions of k general LTFs over {0, 1}n in time poly(n)·2poly(k,1/ε) for all values of k. This algorithm has a poly(n) runtime for k = (log n)c for some absolute constant c > 0, while the previous best poly(n)-time algorithms could only handle k = O(log log n). For intersections of LTFs, by combining these tools with a recent PRG due to [28], we obtain a deterministic algorithm that can approximately count satisfying assignments of intersections of k general LTFs over {0, 1}n in time poly(n) · 2poly(log k,1/ε). This algorithm has a poly(n) runtime for k = 2(log n)c for some absolute constant c > 0, while the previous best poly(n)-time algorithms for intersections of k LTFs, due to [14], could only handle k = O(logloglognn).
KW - Gaussian processes
KW - Johnson-lindenstrauss
KW - Polynomial threshold functions
KW - Pseudorandom generators
UR - http://www.scopus.com/inward/record.url?scp=85070677101&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85070677101&partnerID=8YFLogxK
U2 - 10.4230/LIPIcs.CCC.2019.4
DO - 10.4230/LIPIcs.CCC.2019.4
M3 - Conference contribution
AN - SCOPUS:85070677101
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 34th Computational Complexity Conference, CCC 2019
A2 - Shpilka, Amir
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
T2 - 34th Computational Complexity Conference, CCC 2019
Y2 - 18 July 2019 through 20 July 2019
ER -