Generalized matrix completion and algebraic natural proofs

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Standard

Generalized matrix completion and algebraic natural proofs. / Bläser, Markus; Jindal, Gorav; Ikenmeyer, Christian; Lysikov, Vladimir.

STOC 2018: Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing. New York : Association for Computing Machinery, 2018. s. 17-29 (Proceedings of the Annual ACM Symposium on Theory of Computing).

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Harvard

Bläser, M, Jindal, G, Ikenmeyer, C & Lysikov, V 2018, Generalized matrix completion and algebraic natural proofs. i STOC 2018: Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing. Association for Computing Machinery, New York, Proceedings of the Annual ACM Symposium on Theory of Computing, s. 17-29, 50th Annual ACM Symposium on Theory of Computing, STOC 2018, Los Angeles, USA, 25/06/2018. https://doi.org/10.1145/3188745.3188832

APA

Bläser, M., Jindal, G., Ikenmeyer, C., & Lysikov, V. (2018). Generalized matrix completion and algebraic natural proofs. I STOC 2018: Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing (s. 17-29). Association for Computing Machinery. Proceedings of the Annual ACM Symposium on Theory of Computing https://doi.org/10.1145/3188745.3188832

Vancouver

Bläser M, Jindal G, Ikenmeyer C, Lysikov V. Generalized matrix completion and algebraic natural proofs. I STOC 2018: Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing. New York: Association for Computing Machinery. 2018. s. 17-29. (Proceedings of the Annual ACM Symposium on Theory of Computing). https://doi.org/10.1145/3188745.3188832

Author

Bläser, Markus ; Jindal, Gorav ; Ikenmeyer, Christian ; Lysikov, Vladimir. / Generalized matrix completion and algebraic natural proofs. STOC 2018: Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing. New York : Association for Computing Machinery, 2018. s. 17-29 (Proceedings of the Annual ACM Symposium on Theory of Computing).

Bibtex

@inproceedings{4df5789b35c347e98d5e5fced7f7bf96,
title = "Generalized matrix completion and algebraic natural proofs",
abstract = "Algebraic natural proofs were recently introduced by Forbes, Shpilka and Volk (Proc. of the 49th Annual ACM SIGACT Symposium on Theory of Computing (STOC), pages 653–664, 2017) and independently by Grochow, Kumar, Saks and Saraf (CoRR, abs/1701.01717, 2017) as an attempt to transfer Razborov and Rudich{\textquoteright}s famous barrier result (J. Comput. Syst. Sci., 55(1): 24–35, 1997) for Boolean circuit complexity to algebraic complexity theory. Razborov and Rudich{\textquoteright}s barrier result relies on a widely believed assumption, namely, the existence of pseudo-random generators. Unfortunately, there is no known analogous theory of pseudo-randomness in the algebraic setting. Therefore, Forbes et al. use a concept called succinct hitting sets instead. This assumption is related to polynomial identity testing, but it is currently not clear how plausible this assumption is. Forbes et al. are only able to construct succinct hitting sets against rather weak models of arithmetic circuits. Generalized matrix completion is the following problem: Given a matrix with affine linear forms as entries, find an assignment to the variables in the linear forms such that the rank of the resulting matrix is minimal. We call this rank the completion rank. Computing the completion rank is an NP-hard problem. As our first main result, we prove that it is also NP-hard to determine whether a given matrix can be approximated by matrices of completion rank ≤ b. The minimum quantity b for which this is possible is called border completion rank (similar to the border rank of tensors). Naturally, algebraic natural proofs can only prove lower bounds for such border complexity measures. Furthermore, these border complexity measures play an important role in the geometric complexity program.",
keywords = "Algebraic natural proofs, Completion rank, Geometric complexity theory, Matrix completion, Tensor rank",
author = "Markus Bl{\"a}ser and Gorav Jindal and Christian Ikenmeyer and Vladimir Lysikov",
year = "2018",
month = jun,
day = "20",
doi = "10.1145/3188745.3188832",
language = "English",
series = "Proceedings of the Annual ACM Symposium on Theory of Computing",
publisher = "Association for Computing Machinery",
pages = "17--29",
booktitle = "STOC 2018",
note = "50th Annual ACM Symposium on Theory of Computing, STOC 2018 ; Conference date: 25-06-2018 Through 29-06-2018",

}

RIS

TY - GEN

T1 - Generalized matrix completion and algebraic natural proofs

AU - Bläser, Markus

AU - Jindal, Gorav

AU - Ikenmeyer, Christian

AU - Lysikov, Vladimir

PY - 2018/6/20

Y1 - 2018/6/20

N2 - Algebraic natural proofs were recently introduced by Forbes, Shpilka and Volk (Proc. of the 49th Annual ACM SIGACT Symposium on Theory of Computing (STOC), pages 653–664, 2017) and independently by Grochow, Kumar, Saks and Saraf (CoRR, abs/1701.01717, 2017) as an attempt to transfer Razborov and Rudich’s famous barrier result (J. Comput. Syst. Sci., 55(1): 24–35, 1997) for Boolean circuit complexity to algebraic complexity theory. Razborov and Rudich’s barrier result relies on a widely believed assumption, namely, the existence of pseudo-random generators. Unfortunately, there is no known analogous theory of pseudo-randomness in the algebraic setting. Therefore, Forbes et al. use a concept called succinct hitting sets instead. This assumption is related to polynomial identity testing, but it is currently not clear how plausible this assumption is. Forbes et al. are only able to construct succinct hitting sets against rather weak models of arithmetic circuits. Generalized matrix completion is the following problem: Given a matrix with affine linear forms as entries, find an assignment to the variables in the linear forms such that the rank of the resulting matrix is minimal. We call this rank the completion rank. Computing the completion rank is an NP-hard problem. As our first main result, we prove that it is also NP-hard to determine whether a given matrix can be approximated by matrices of completion rank ≤ b. The minimum quantity b for which this is possible is called border completion rank (similar to the border rank of tensors). Naturally, algebraic natural proofs can only prove lower bounds for such border complexity measures. Furthermore, these border complexity measures play an important role in the geometric complexity program.

AB - Algebraic natural proofs were recently introduced by Forbes, Shpilka and Volk (Proc. of the 49th Annual ACM SIGACT Symposium on Theory of Computing (STOC), pages 653–664, 2017) and independently by Grochow, Kumar, Saks and Saraf (CoRR, abs/1701.01717, 2017) as an attempt to transfer Razborov and Rudich’s famous barrier result (J. Comput. Syst. Sci., 55(1): 24–35, 1997) for Boolean circuit complexity to algebraic complexity theory. Razborov and Rudich’s barrier result relies on a widely believed assumption, namely, the existence of pseudo-random generators. Unfortunately, there is no known analogous theory of pseudo-randomness in the algebraic setting. Therefore, Forbes et al. use a concept called succinct hitting sets instead. This assumption is related to polynomial identity testing, but it is currently not clear how plausible this assumption is. Forbes et al. are only able to construct succinct hitting sets against rather weak models of arithmetic circuits. Generalized matrix completion is the following problem: Given a matrix with affine linear forms as entries, find an assignment to the variables in the linear forms such that the rank of the resulting matrix is minimal. We call this rank the completion rank. Computing the completion rank is an NP-hard problem. As our first main result, we prove that it is also NP-hard to determine whether a given matrix can be approximated by matrices of completion rank ≤ b. The minimum quantity b for which this is possible is called border completion rank (similar to the border rank of tensors). Naturally, algebraic natural proofs can only prove lower bounds for such border complexity measures. Furthermore, these border complexity measures play an important role in the geometric complexity program.

KW - Algebraic natural proofs

KW - Completion rank

KW - Geometric complexity theory

KW - Matrix completion

KW - Tensor rank

UR - http://www.scopus.com/inward/record.url?scp=85049907649&partnerID=8YFLogxK

U2 - 10.1145/3188745.3188832

DO - 10.1145/3188745.3188832

M3 - Article in proceedings

AN - SCOPUS:85049907649

T3 - Proceedings of the Annual ACM Symposium on Theory of Computing

SP - 17

EP - 29

BT - STOC 2018

PB - Association for Computing Machinery

CY - New York

T2 - 50th Annual ACM Symposium on Theory of Computing, STOC 2018

Y2 - 25 June 2018 through 29 June 2018

ER -

ID: 232711612