Tensor Reconstruction Beyond Constant Rank

Authors Shir Peleg , Amir Shpilka , Ben Lee Volk



PDF
Thumbnail PDF

File

LIPIcs.ITCS.2024.87.pdf
  • Filesize: 0.85 MB
  • 20 pages

Document Identifiers

Author Details

Shir Peleg
  • Blavatnik School of Computer Science, Tel Aviv University, Israel
Amir Shpilka
  • Blavatnik School of Computer Science, Tel Aviv University, Israel
Ben Lee Volk
  • Efi Arazi School of Computer Science, Reichman University, Herlizya, Israel

Cite AsGet BibTex

Shir Peleg, Amir Shpilka, and Ben Lee Volk. Tensor Reconstruction Beyond Constant Rank. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 87:1-87:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.ITCS.2024.87

Abstract

We give reconstruction algorithms for subclasses of depth-3 arithmetic circuits. In particular, we obtain the first efficient algorithm for finding tensor rank, and an optimal tensor decomposition as a sum of rank-one tensors, when given black-box access to a tensor of super-constant rank. Specifically, we obtain the following results: 1) A deterministic algorithm that reconstructs polynomials computed by Σ^{[k]}⋀^{[d]}Σ circuits in time poly(n,d,c) ⋅ poly(k)^{k^{k^{10}}}, 2) A randomized algorithm that reconstructs polynomials computed by multilinear Σ^{[k]}∏^{[d]}Σ circuits in time poly(n,d,c) ⋅ k^{k^{k^{k^{O(k)}}}}, 3) A randomized algorithm that reconstructs polynomials computed by set-multilinear Σ^{[k]}∏^{[d]}Σ circuits in time poly(n,d,c) ⋅ k^{k^{k^{k^{O(k)}}}}, where c = log q if 𝔽 = 𝔽_q is a finite field, and c equals the maximum bit complexity of any coefficient of f if 𝔽 is infinite. Prior to our work, polynomial time algorithms for the case when the rank, k, is constant, were given by Bhargava, Saraf and Volkovich [Vishwas Bhargava et al., 2021]. Another contribution of this work is correcting an error from a paper of Karnin and Shpilka [Zohar Shay Karnin and Amir Shpilka, 2009] (with some loss in parameters) that also affected Theorem 1.6 of [Vishwas Bhargava et al., 2021]. Consequently, the results of [Zohar Shay Karnin and Amir Shpilka, 2009; Vishwas Bhargava et al., 2021] continue to hold, with a slightly worse setting of parameters. For fixing the error we systematically study the relation between syntactic and semantic notions of rank of Σ Π Σ circuits, and the corresponding partitions of such circuits. We obtain our improved running time by introducing a technique for learning rank preserving coordinate-subspaces. Both [Zohar Shay Karnin and Amir Shpilka, 2009] and [Vishwas Bhargava et al., 2021] tried all choices of finding the "correct" coordinates, which, due to the size of the set, led to having a fast growing function of k at the exponent of n. We manage to find these spaces in time that is still growing fast with k, yet it is only a fixed polynomial in n.

Subject Classification

ACM Subject Classification
  • Theory of computation → Algebraic complexity theory
Keywords
  • Algebraic circuits
  • reconstruction
  • tensor decomposition
  • tensor rank

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. Manindra Agrawal, Rohit Gurjar, Arpita Korwar, and Nitin Saxena. Hitting-sets for ROABP and sum of set-multilinear circuits. SIAM Journal of Computing, 44(3):669-697, 2015. URL: https://doi.org/10.1137/140975103.
  2. Manindra Agrawal and V. Vinay. Arithmetic circuits: A chasm at depth four. In Proceedings of the 49th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2008), pages 67-75, 2008. URL: https://doi.org/10.1109/FOCS.2008.32.
  3. Michael Ben-Or and Prasoon Tiwari. A deterministic algorithm for sparse multivariate polynominal interpolation (extended abstract). In Proceedings of the 20th Annual ACM Symposium on Theory of Computing (STOC 1988), pages 301-309. ACM, 1988. URL: https://doi.org/10.1145/62212.62241.
  4. Vishwas Bhargava, Shubhangi Saraf, and Ilya Volkovich. Reconstruction of depth-4 multilinear circuits. In Proceedings of the 31st Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2020), pages 2144-2160. SIAM, 2020. URL: https://doi.org/10.1137/1.9781611975994.132.
  5. Vishwas Bhargava, Shubhangi Saraf, and Ilya Volkovich. Reconstruction algorithms for low-rank tensors and depth-3 multilinear circuits. In Proceedings of the 53rd Annual ACM Symposium on Theory of Computing (STOC 2021), pages 809-822. ACM, 2021. URL: https://doi.org/10.1145/3406325.3451096.
  6. Markus Bläser, Christian Ikenmeyer, Gorav Jindal, and Vladimir Lysikov. Generalized matrix completion and algebraic natural proofs. In Proceedings of the 50th Annual ACM Symposium on Theory of Computing (STOC 2018), pages 1193-1206. ACM, 2018. URL: https://doi.org/10.1145/3188745.3188832.
  7. Nader H. Bshouty. Exact learning from membership queries: Some techniques, results and new directions. In Algorithmic Learning Theory - 24th International Conference, ALT 2013, volume 8139 of Lecture Notes in Computer Science, pages 33-52. Springer, 2013. URL: https://doi.org/10.1007/978-3-642-40935-6_4.
  8. Enrico Carlini. Reducing the number of variables of a polynomial. In Algebraic Geometry and Geometric Modeling, pages 237-247, 2006. URL: https://doi.org/10.1007/978-3-540-33275-6_15.
  9. David A. Cox, John B. Little, and Donal O'Shea. Ideals, Varieties and Algorithms. Undergraduate texts in mathematics. Springer, 2007. URL: https://doi.org/10.1007/978-0-387-35651-8.
  10. Zeev Dvir and Amir Shpilka. Locally decodable codes with two queries and polynomial identity testing for depth 3 circuits. SIAM J. Comput., 36(5):1404-1434, 2007. Preliminary version in the 37th Annual ACM Symposium on Theory of Computing (STOC 2005). URL: https://doi.org/10.1137/05063605X.
  11. Michael A. Forbes, Ramprasad Saptharishi, and Amir Shpilka. Hitting sets for multilinear read-once algebraic branching programs, in any order. In Proceedings of the 46th Annual ACM Symposium on Theory of Computing (STOC 2014), pages 867-875, 2014. URL: https://doi.org/10.1145/2591796.2591816.
  12. Michael A. Forbes and Amir Shpilka. Quasipolynomial-time identity testing of non-commutative and read-once oblivious algebraic branching programs. In Proceedings of the 54th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2013), pages 243-252, 2013. Full version at http://arxiv.org/abs/1209.2408. URL: https://doi.org/10.1109/FOCS.2013.34.
  13. Ankit Garg, Neeraj Kayal, and Chandan Saha. Learning sums of powers of low-degree polynomials in the non-degenerate case. In Proceedings of the 61st Annual IEEE Symposium on Foundations of Computer Science (FOCS 2020), pages 889-899. IEEE, 2020. URL: https://doi.org/10.1109/FOCS46700.2020.00087.
  14. Zeyu Guo and Rohit Gurjar. Improved explicit hitting-sets for roabps. In Proceedings of the 24th International Workshop on Randomization and Computation (RANDOM 2020), volume 176 of LIPIcs, pages 4:1-4:16, 2020. URL: https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2020.4.
  15. Ankit Gupta, Pritish Kamath, Neeraj Kayal, and Ramprasad Saptharishi. Arithmetic circuits: A chasm at depth 3. SIAM J. Comput., 45(3):1064-1079, 2016. URL: https://doi.org/10.1137/140957123.
  16. Ankit Gupta, Neeraj Kayal, and Satyanarayana V. Lokam. Efficient reconstruction of random multilinear formulas. In Proceedings of the 52nd Annual IEEE Symposium on Foundations of Computer Science (FOCS 2011), pages 778-787. IEEE Computer Society, 2011. URL: https://doi.org/10.1109/FOCS.2011.70.
  17. Ankit Gupta, Neeraj Kayal, and Satyanarayana V. Lokam. Reconstruction of depth-4 multilinear circuits with top fan-in 2. In Proceedings of the 44th Annual ACM Symposium on Theory of Computing (STOC 2012), pages 625-642. ACM, 2012. URL: https://doi.org/10.1145/2213977.2214035.
  18. Johan Håstad. Tensor rank is np-complete. J. Algorithms, 11(4):644-654, 1990. URL: https://doi.org/10.1016/0196-6774(90)90014-6.
  19. Zohar Shay Karnin and Amir Shpilka. Black box polynomial identity testing of generalized depth-3 arithmetic circuits with bounded top fan-in. In Proceedings of the 23rd Annual IEEE Conference on Computational Complexity, CCC 2008, 23-26 June 2008, College Park, Maryland, USA, pages 280-291. IEEE Computer Society, 2008. URL: https://doi.org/10.1109/CCC.2008.15.
  20. Zohar Shay Karnin and Amir Shpilka. Reconstruction of generalized depth-3 arithmetic circuits with bounded top fan-in. In Proceedings of the 24th Annual Computational Complexity Conference (CCC 2009), pages 274-285. IEEE Computer Society, 2009. URL: https://doi.org/10.1109/CCC.2009.18.
  21. Neeraj Kayal. Efficient algorithms for some special cases of the polynomial equivalence problem. In Proceedings of the 22nd Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2011), pages 1409-1421. SIAM, 2011. URL: https://doi.org/10.1137/1.9781611973082.108.
  22. Neeraj Kayal, Vineet Nair, and Chandan Saha. Average-case linear matrix factorization and reconstruction of low width algebraic branching programs. Comput. Complex., 28(4):749-828, 2019. URL: https://doi.org/10.1007/s00037-019-00189-0.
  23. Neeraj Kayal and Shubhangi Saraf. Blackbox polynomial identity testing for depth-3 circuits. In Proceedings of the 50th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2009), 2009. URL: https://doi.org/10.1109/FOCS.2009.67.
  24. Adam Klivans and Daniel A. Spielman. Randomness efficient identity testing of multivariate polynomials. In Proceedings of the 33rd Annual ACM Symposium on Theory of Computing (STOC 2001), pages 216-223, 2001. URL: https://doi.org/10.1145/380752.380801.
  25. Pascal Koiran. Arithmetic circuits: The chasm at depth four gets wider. Theoretical Computer Science, 448:56-65, 2012. URL: https://doi.org/10.1016/j.tcs.2012.03.041.
  26. Nitin Saxena and C. Seshadhri. An almost optimal rank bound for depth-3 identities. SIAM J. Comput., 40(1):200-224, 2011. URL: https://doi.org/10.1137/090770679.
  27. Nitin Saxena and C. Seshadhri. Blackbox identity testing for bounded top-fanin depth-3 circuits: The field doesn't matter. SIAM J. Comput., 41(5):1285-1298, 2012. Preliminary version in the 43rd Annual ACM Symposium on Theory of Computing (STOC 2011). URL: https://doi.org/10.1137/10848232.
  28. Nitin Saxena and C. Seshadhri. From sylvester-gallai configurations to rank bounds: Improved blackbox identity test for depth-3 circuits. J. ACM, 60(5):33:1-33:33, 2013. URL: https://doi.org/10.1145/2528403.
  29. Yaroslav Shitov. How hard is the tensor rank? arXiv preprint, 2016. URL: https://arxiv.org/abs/1611.01559.
  30. Amir Shpilka and Amir Yehudayoff. Arithmetic circuits: A survey of recent results and open questions. Foundations and Trends in Theoretical Computer Science, 5:207-388, March 2010. URL: https://doi.org/10.1561/0400000039.
  31. Gaurav Sinha. Reconstruction of real depth-3 circuits with top fan-in 2. In Proceedings of the 31st Annual Computational Complexity Conference (CCC 2016), volume 50 of LIPIcs, pages 31:1-31:53, 2016. URL: https://doi.org/10.4230/LIPIcs.CCC.2016.31.
  32. Gaurav Sinha. Efficient reconstruction of depth three arithmetic circuits with top fan-in two. In Mark Braverman, editor, Proceedings of the 13th Innovations in Theoretical Computer Science Conference (ICTS 2022), volume 215 of LIPIcs, pages 118:1-118:33. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. URL: https://doi.org/10.4230/LIPIcs.ITCS.2022.118.
  33. Joseph Swernofsky. Tensor rank is hard to approximate. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2018, volume 116 of LIPIcs, pages 26:1-26:9, 2018. URL: https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2018.26.
  34. Sébastien Tavenas. Improved bounds for reduction to depth 4 and depth 3. Inf. Comput., 240:2-11, 2015. Preliminary version in the 38th International Symposium on the Mathematical Foundations of Computer Science (MFCS 2013). URL: https://doi.org/10.1016/j.ic.2014.09.004.
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail