The DOI matches its Crossref record; 7 of the 8 references it cites were found in a registry or an index.
Matrix multiplication via arithmetic progressions
Open accessOverview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“With the use of the Coppersmith-Winograd algorithm, the time complexity of both the KF-based algorithms can be reduced from O ( m 3 ) to O ( m 2 . 375 ) .”
From Real-Time Performance Assessment of High-Order Tremor Estimators Used in a Wearable Tremor Suppression Device (2022) · cites this paper as [41]
In the citing paper
“Therefore, to reduce the time complexity of the KFbased algorithms, a Coppersmith-Winograd algorithm [41] can be used to optimize the matrix operation.”
From Real-Time Performance Assessment of High-Order Tremor Estimators Used in a Wearable Tremor Suppression Device (2022) · cites this paper as [41]
In the citing paper
“It was identified that the use of a Coppersmith-Winograd algorithm can largely reduce the time complexity of the KFbased algorithm to a similar level as the BMFLC.”
From Real-Time Performance Assessment of High-Order Tremor Estimators Used in a Wearable Tremor Suppression Device (2022) · cites this paper as [41]
Citations
Cites
On Sets of Integers Which Contain No Three Terms in Arithmetical Progression
Behrend, F. A. (1946) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.32.12.331 · Cited by 414
Partial and Total Matrix Multiplication
Schönhage, A. (1981) · SIAM Journal on Computing · doi:10.1137/0210032 · Cited by 279
On the Asymptotic Complexity of Matrix Multiplication
Coppersmith, D., & Winograd, S. (1982) · SIAM Journal on Computing · doi:10.1137/0211038 · Cited by 221
Self-citationHow to Multiply Matrices Faster
(1984) · Lecture notes in computer science · doi:10.1007/3-540-13866-8 · Cited by 147
On Sets of Integers Which Contain No Three Terms in Arithmetical Progression
Salem, R., & Spencer, D. C. (1942) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.28.12.561 · Cited by 134
Pan, V. Y. (1978) · Annual Symposium on Foundations of Computer Science · doi:10.1109/sfcs.1978.34 · Cited by 121
The asymptotic spectrum of tensors and the exponent of matrix multiplication
Strassen, V. (1986) · Annual Symposium on Foundations of Computer Science · doi:10.1109/sfcs.1986.52 · Cited by 120
Cited by
Sorted by citations
Items 601–700 of 1,001
Parberry, I. (1995) · ACM SIGACT News · doi:10.1145/202840.606479 · Cited by 27
Using fast matrix multiplication to find basic solutions
Beling, P. A., & Megiddo, N. (1998) · Theoretical Computer Science · doi:10.1016/s0304-3975(98)00003-6 · Cited by 27
Low-Complexity LMMSE-Based MIMO-OFDM Channel Estimation Via Angle-Domain Processing
Huang, L., Bergmans, J. W. M., & Willems, F. M. J. (2007) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2007.901133 · Cited by 27
Parameterized Computation and Complexity: A New Approach Dealing with NP-Hardness
Chen, J. (2005) · Journal of Computer Science and Technology · doi:10.1007/s11390-005-0003-7 · Cited by 27
Additive preconditioning and aggregation in matrix computations
Pan, V. Y., Ivolgin, D., Murphy, B., Rosholt, R. E., Taj-Eddin, I., Tang, Y., & Yan, X. (2007) · Computers & Mathematics with Applications · doi:10.1016/j.camwa.2004.03.022 · Cited by 27
Kumar, P. (2003) · Cited by 27
Parallel computation of polynomial GCD and some related parallel computations over abstract fields
Pan, V. Y. (1996) · Theoretical Computer Science · doi:10.1016/0304-3975(96)00030-8 · Cited by 27
Computations for algebras and group representations
Eberly, W., & Gathen, J. V. Z. (1989) · Cited by 27
Abusing the Tutte Matrix: An Algebraic Instance Compression for the K-set-cycle ProblemPreprint
Wahlström, M. (2013) · arXiv (Cornell University) · doi:10.4230/lipics.stacs.2013.341 · Cited by 27
Eine kritische Analyse von Vernetzungsmaßen in sozialen Netzwerken
Landherr, A., Friedl, B., & Heidemann, J. (2010) · WIRTSCHAFTSINFORMATIK · doi:10.1007/s11576-010-0244-0 · Cited by 26
Social network document ranking
Gou, L., Zhang, X., Chen, H., Kim, J.-H., & Giles, C. L. (2010) · ACM/IEEE Joint Conference on Digital Libraries · doi:10.1145/1816123.1816170 · Cited by 27
Matrix Multiplication, a Little Faster
Karstadt, E., & Schwartz, O. (2017) · ACM Symposium on Parallelism in Algorithms and Architectures (SPAA) · doi:10.1145/3087556.3087579 · Cited by 37
Partitioning into Sets of Bounded Cardinality
Koivisto, M. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-11269-0_21 · Cited by 30
Ideal forms of Coppersmith's theorem and Guruswami-Sudan list decoding
Cohn, H., & Heninger, N. (2015) · Advances in Mathematics of Communications · doi:10.3934/amc.2015.9.311 · Cited by 26
Kaplan, H. Y., Rubin, N., Sharir, M., & Verbin, E. (2007) · doi:10.5555/1283383.1283467 · Cited by 26
SETH-Based Lower Bounds for Subset Sum and Bicriteria Path
Abboud, A., Bringmann, K., Hermelin, D., & Shabtay, D. (2019) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611975482.3 · Cited by 26
Joint metric and feature representation learning for unsupervised domain adaptation
Xie, Y., Du, Z., Li, J., Jing, M., Chen, E., & Lü, K. (2019) · Knowledge-Based Systems · doi:10.1016/j.knosys.2019.105222 · Cited by 26
A Quantum Computational Approach to Correspondence Problems on Point Sets
Golyanik, V., & Theobalt, C. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00920 · Cited by 26
Bini, D. A. (2013) · Discrete mathematics and its applications · doi:10.1201/b16113-72 · Cited by 26
Communication Efficient Secure Linear Algebra
Kobbi Nissim, B., & Weinreb, E. (2006) · Lecture notes in computer science · doi:10.1007/11681878_27 · Cited by 26
Grids: A Domain for Analyzing the Distribution of Numerical Values
Roberto Bagnara, A., Dobson, K., Hill, P. M., Mundell, M., & Enea Zaffanella, A. (2007) · Springer eBooks · doi:10.1007/978-3-540-71410-1_16 · Cited by 26
Messages versus Messengers in Distributed Programming
Fukuda, M., Bic, L., Dillencourt, M. B., & Cahill, J. M. (1999) · Journal of Parallel and Distributed Computing · doi:10.1006/jpdc.1999.1533 · Cited by 26
Zwick, U. (2006) · Algorithmica · doi:10.1007/s00453-005-1199-1 · Cited by 26
Enumerating the Junction Trees of a Decomposable Graph
Thomas, A., & Green, P. J. (2009) · Journal of Computational and Graphical Statistics · doi:10.1198/jcgs.2009.07129 · Cited by 27
Matrix representation of conflicts with two decision-makers
Xu, H., Hipel, K. W., & Kilgour, D. M. (2007) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2007.4413988 · Cited by 26
Efficient Triangle Counting in Large Graphs via Degree-Based Vertex Partitioning
Kolountzakis, M. N., Miller, G. L., Peng, R., & Tsourakakis, C. E. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-18009-5_3 · Cited by 26
Li, K. (1997) · The Journal of Supercomputing · doi:10.1023/a:1007922924139 · Cited by 26
Load-Balancing Scheme With Small-Cell Cooperation for Clustered Heterogeneous Cellular Networks
Park, J., & Kim, K. S. (2017) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2017.2748570 · Cited by 25
Matrix Multiplication, a Little Faster
Karstadt, E., & Schwartz, O. (2020) · Journal of the ACM · doi:10.1145/3364504 · Cited by 32
Remote State Estimation of Nonlinear Systems Over Fading Channels via Recurrent Neural Networks
Cai, S., & Lau, V. K. N. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3054826 · Cited by 25
Time-work tradeoffs for parallel algorithms
Spencer, T. H. (1997) · Journal of the ACM · doi:10.1145/265910.265923 · Cited by 25
Spectral Counting of Triangles in Power-Law Networks via Element-Wise Sparsification
Tsourakakis, C. E., Petros Drineas, B., Michelakis, E., Koutis, I., & Faloutsos, C. (2009) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1109/asonam.2009.32 · Cited by 25
Estimating all pairs shortest paths in restricted graph families: a unified approach
Dragan, F. F. (2004) · Journal of Algorithms · doi:10.1016/j.jalgor.2004.09.002 · Cited by 25
Triangulated neighborhoods in even-hole-free graphs
da Silva, M. V. G., & Vušković, K. (2006) · Discrete Mathematics · doi:10.1016/j.disc.2006.07.027 · Cited by 25
Efficient orbit-aware triad and quad census in directed and undirected graphs
Ortmann, M., & Brandes, U. (2017) · Applied Network Science · doi:10.1007/s41109-017-0027-2 · Cited by 25
Auto-Tuning CNNs for Coarse-Grained Reconfigurable Array-Based Accelerators
Bae, I., Harris, B., Min, H., & Egger, B. (2018) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2018.2857278 · Cited by 25
Czapla, B., & Narayanaswamy, A. (2019) · Journal of Quantitative Spectroscopy and Radiative Transfer · doi:10.1016/j.jqsrt.2019.01.020 · Cited by 25
Efficient Deterministic Algorithms for Finding a Minimum Cycle Basis in Undirected Graphs
Amaldi, E., Iuliano, C., & Rizzi, R. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13036-6_30 · Cited by 25
Expressing a fraction of two determinants as a determinant
Kaltofen, E., & Koiran, P. (2008) · International Symposium on Symbolic and Algebraic Computation · doi:10.1145/1390768.1390790 · Cited by 25
Sparse Recovery using Smoothed $\ell^0$ (SL0): Convergence AnalysisPreprint
Mohimani, H., Babaie‐Zadeh, M., Gorodnitsky, I. F., & Christian Jutten, B. (2010) · arXiv (Cornell University) · doi:10.48550/arxiv.1001.5073 · Cited by 25
Fast Dynamic Transitive Closure with Lookahead
Sankowski, P., & Mucha, M. (2008) · Algorithmica · doi:10.1007/s00453-008-9166-2 · Cited by 24
Tangent space spatial filters for interpretable and efficient Riemannian classification
Xu, J., Grosse‐Wentrup, M., & Jayaram, V. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab839e · Cited by 24
Codes Trading Upload for Download Cost in Secure Distributed Matrix Multiplication
Kakar, J., Khristoforov, A., Ebadifar, S., & Sezgin, A. (2021) · IEEE Transactions on Communications · doi:10.1109/tcomm.2021.3083730 · Cited by 25
Fast Parsing for Boolean Grammars: A Generalization of Valiant’s Algorithm
Okhotin, A. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-14455-4_31 · Cited by 24
Improved decremental algorithms for maintaining transitive closure and all-pairs shortest paths
Baswana, S., Hariharan, R., & Sen, S. (2002) · ACM Symposium on Theory of Computing (STOC) · doi:10.1145/509907.509928 · Cited by 24
Unifying Known Lower Bounds via Geometric Complexity Theory
Grochow, J. A. (2015) · Computational Complexity · doi:10.1007/s00037-015-0103-x · Cited by 24
An approach to model building for accelerated cooling process using instance-based learning
Zheng, Y., Li, S., & Wang, X. (2010) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.01.020 · Cited by 24
A tight bound for Green's arithmetic triangle removal lemma in vector spaces
Fox, J., & Lovász, L. M. (2017) · Advances in Mathematics · doi:10.1016/j.aim.2017.09.037 · Cited by 24
A Fast Algorithm for Convolutional Neural Networks Using Tile-based Fast Fourier Transforms
Lin, J., & Yao, Y. (2019) · Neural Processing Letters · doi:10.1007/s11063-019-09981-z · Cited by 24
Alagapan, S., Shin, H. W., Frӧhlich, F., & Wu, H. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aaf2ba · Cited by 24
Subcubic algorithms for Gomory–Hu tree in unweighted graphs
Abboud, A., Krauthgamer, R., & Trabelsi, O. (2021) · ACM Symposium on Theory of Computing (STOC) · doi:10.1145/3406325.3451073 · Cited by 24
Adaptive Strassen's matrix multiplication
D’Alberto, P., & Nicolau, A. E. (2007) · International Conference on Supercomputing · doi:10.1145/1274971.1275010 · Cited by 25
Maximum matching in graphs with an excluded minor
Yuster, R., & Zwick, U. (2007) · doi:10.5555/1283383.1283396 · Cited by 24
Explicit Dimension Reduction and Its Applications
Karnin, Z. S., Rabani, Y., & Shpilka, A. (2011) · IEEE Conference on Computational Complexity (CCC) · doi:10.1109/ccc.2011.20 · Cited by 24
Fast estimation of diameter and shortest paths (without matrix multiplication)
Aingworth, D., Chekuri, C., & Motwani, R. (1996) · Symposium on Discrete Algorithms · doi:10.5555/313852.314117 · Cited by 24
Advanced document description, a sequential approach
Doucet, A. (2006) · ACM SIGIR Forum · doi:10.1145/1147197.1147212 · Cited by 24
Error Compensation in Leaf Root Problems
Dom, M., Guo, J., Hüffner, F., & Niedermeier, R. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30551-4_35 · Cited by 24
Computing the diameter polynomially faster than APSPPreprint
Yuster, R. (2010) · arXiv (Cornell University) · doi:10.48550/arxiv.1011.6181 · Cited by 24
Highly Parallel Sparse Matrix-Matrix MultiplicationPreprint
Buluç, A., & Gilbert, J. R. (2010) · arXiv (Cornell University) · doi:10.48550/arxiv.1006.2183 · Cited by 24
On the computational complexity of Betti numbers: reductions from matrix rank
Edelsbrunner, H., & Parsa, S. (2014) · doi:10.5555/2634074.2634085 · Cited by 23
Fast computation of common left multiples of linear ordinary differential operators
Bostan, A., Chyzak, F., Salvy, B., & Li, Z. (2012) · International Symposium on Symbolic and Algebraic Computation · doi:10.1145/2442829.2442847 · Cited by 23
Multi-source domain adaptation with graph embedding and adaptive label prediction
Ma, A., You, F., Jing, M., Li, J., & Lü, K. (2020) · Information Processing & Management · doi:10.1016/j.ipm.2020.102367 · Cited by 23
A New Combinatorial Approach for Sparse Graph Problems
Blelloch, G. E., Williams, V. V., & Williams, R. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-70575-8_10 · Cited by 23
Calculating Excited States of Molecular Aggregates by the Renormalized Excitonic Method
Ma, Y., & Ma, H. (2013) · The Journal of Physical Chemistry A · doi:10.1021/jp401168s · Cited by 23
Goodness-of-Fit Measures for Revealed Preference Tests
Smeulders, B., Spieksma, F. C. R., Cherchye, L., & Bram De Rock, Z. (2014) · ACM Transactions on Economics and Computation · doi:10.1145/2560793 · Cited by 23
Hybrid Energy Harvesting Wireless Systems: Performance Evaluation and Benchmarking
Rao, S., & Mehta, N. B. (2014) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2014.2331978 · Cited by 23
Compressed matrix multiplication
Pagh, R. (2012) · Conference on Innovations in Theoretical Computer Science · doi:10.1145/2090236.2090271 · Cited by 23
New algorithms and hardness for incremental single-source shortest paths in directed graphs
Gutenberg, M. P., Williams, V. V., & Wein, N. (2020) · ACM Symposium on Theory of Computing (STOC) · doi:10.1145/3357713.3384236 · Cited by 33
Accelerating Strassen-Winograd's matrix multiplication algorithm on GPUs
Lai, P.-W., Arafat, H., Elango, V., & Sadayappan, P. (2013) · IEEE International Conference on High Performance Computing, Data, and Analytics · doi:10.1109/hipc.2013.6799109 · Cited by 24
Relative Rigid Cohomology and Deformation of Hypersurfaces
Gerkmann, R. (2008) · International Mathematics Research Papers · doi:10.1093/imrp/rpm003 · Cited by 23
Neiger, V. (2016) · International Symposium on Symbolic and Algebraic Computation · doi:10.1145/2930889.2930936 · Cited by 23
Modular code generation from synchronous block diagrams
Lublinerman, R., Szegedy, C., & Tripakis, S. (2009) · ACM SIGPLAN Notices · doi:10.1145/1594834.1480893 · Cited by 23
Asymptotical Structure of Combinatorial Objects
Dvořák, Z. (2007) · Digital Repository (National Repository of Grey Literature) · Cited by 23
Communication-efficient parallel generic pairwise elimination
Tiskin, A. (2006) · Future Generation Computer Systems · doi:10.1016/j.future.2006.04.017 · Cited by 22
Robust CDMA multiuser detection using a neural-network approach
Chuah, T. C., Sharif, B. S., & Hinton, O. R. (2002) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2002.804310 · Cited by 22
Core Stability of Minimum Coloring Games
Bietenhader, T., & Okamoto, Y. (2006) · Mathematics of Operations Research · doi:10.1287/moor.1060.0187 · Cited by 22
Complexity of the path avoiding forbidden pairs problem revisited
Kováč, J. (2013) · Discrete Applied Mathematics · doi:10.1016/j.dam.2012.12.022 · Cited by 22
INTRODUCTION TO FIXED-PARAMETER ALGORITHMS
Niedermeier, R. (2006) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198566076.003.0001 · Cited by 22
Convolution Accelerator Designs Using Fast Algorithms
Zhao, Y., Wang, D., & Wang, L. (2019) · Algorithms · doi:10.3390/a12050112 · Cited by 22
A linear algebraic approach to datalog evaluation
Sato, T. (2017) · Theory and Practice of Logic Programming · doi:10.1017/s1471068417000023 · Cited by 22
On approximation of 2D persistence modules by interval-decomposables
Asashiba, H., Escolar, E. G., Nakashima, K., & Yoshiwaki, M. (2023) · Journal of Computational Algebra · doi:10.1016/j.jaca.2023.100007 · Cited by 22
Efficient Decomposition of Associative Algebras over Finite Fields
Eberly, W., & Giesbrecht, M. W. (2000) · Journal of Symbolic Computation · doi:10.1006/jsco.1999.0308 · Cited by 22
Modular Composition Modulo Triangular Sets and Applications
Poteaux, A., & Schost, É. (2013) · Computational Complexity · doi:10.1007/s00037-013-0063-y · Cited by 22
Growth Functions and Automatic Groups
Epstein, D. B. A., lano-Fletcher, A. R., & Zwick, U. (1996) · Experimental Mathematics · doi:10.1080/10586458.1996.10504595 · Cited by 22
Akutsu, T., Miyano, S., & Kuhara, S. (2000) · Research in Computational Molecular Biology · doi:10.1145/332306.332317 · Cited by 22
Some Prospects forEfficient Fixed Parameter Algorithms
Niedermeier, R. (1998) · Lecture notes in computer science · doi:10.1007/3-540-49477-4_12 · Cited by 22
Stochastic Optimization for Machine LearningPreprint
Cotter, A. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1308.3509 · Cited by 22
Algorithm Design Using Spectral Graph Theory
Peng, R. (2013) · Figshare · doi:10.1184/r1/6714635 · Cited by 23
Products of ordinary differential operators by evaluation and interpolation
Bostan, A., Chyzak, F., & Roux, N. L. (2008) · International Symposium on Symbolic and Algebraic Computation · doi:10.1145/1390768.1390775 · Cited by 21
Finding a Heaviest Vertex-Weighted Triangle Is not Harder than Matrix Multiplication
Czumaj, A., & Andrzej Lingas, B. (2009) · SIAM Journal on Computing · doi:10.1137/070695149 · Cited by 21
Minimum Weight Cycles and Triangles: Equivalences and Algorithms
Roditty, L., & Williams, V. V. (2011) · Annual Symposium on Foundations of Computer Science · doi:10.1109/focs.2011.27 · Cited by 21
A Novel Transmitter-Based Selective-Precoding Technique for DS/CDMA Systems
Masouros, C., & Alsusa, E. A. (2007) · International Conference on Communications · doi:10.1109/icc.2007.470 · Cited by 21
Auction-Based On-Demand P2P Min-Cost Media Streaming with Network Coding
Chu, X., Zhao, K., Li, Z., & Mahanti, A. (2009) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2009.40 · Cited by 21
Gou, L., Chen, H., Kim, J.-H., Zhang, X., & Giles, C. L. (2010) · Multimedia Information Retrieval · doi:10.1145/1743384.1743443 · Cited by 22
Adaptive complementary filtering algorithm for mobile robot localization
Neto, A. A., Macharet, D. G., Campos, V. C. D. S., & Campos, M. F. M. (2009) · Journal of the Brazilian Computer Society · doi:10.1007/bf03194503 · Cited by 21
Accelerating Matrix Multiplication in Deep Learning by Using Low-Rank Approximation
Osawa, K., Sekiya, A., Naganuma, H., & Yokota, R. (2017) · International Conference on High Performance Computing & Simulation (HPCS) · doi:10.1109/hpcs.2017.37 · Cited by 21
Interface Reduction with Multilevel Craig–Bampton Substructuring for Component Mode Synthesis
Wu, L., Tiso, P., & van Keulen, F. (2018) · AIAA Journal · doi:10.2514/1.j056196 · Cited by 21
Scalability and robustness of spectral embedding: landmark diffusion is all you need
Shen, C., & Wu, H. (2022) · Information and Inference A Journal of the IMA · doi:10.1093/imaiai/iaac013 · Cited by 21
A quantum interior-point predictor–corrector algorithm for linear programming
Casares, P. A. M., & Martin-Delgado, M. A. (2020) · Journal of Physics A Mathematical and Theoretical · doi:10.1088/1751-8121/abb439 · Cited by 24
Efficient Statistical Model for Predicting Electromagnetic Wave Distribution in Coupled Enclosures
Ma, S., Phang, S., Drikas, Z., Addissie, B., Hong, R., Blakaj, V., Gradoni, G., Tanner, G., Antonsen, T. M., Ott, E., et al. (2020) · Physical Review Applied · doi:10.1103/physrevapplied.14.014022 · Cited by 21
Metadata
- Authors
- Coppersmith, D., & Winograd, S.
- Affiliations
- IBM Research - Thomas J. Watson Research Center (US)
- Venue
- Journal of Symbolic Computation
- Publisher
- Elsevier BV
- Published
- 1990-03
- Volume
- 9
- Issue
- 3
- Pages
- 251-280
- ISSN
- 0747-7171 (ISSN-L)
- OpenAlex
- W1979740015
- Cited by
- 2,248
- References
- 8
- Citations by year
- 2026: 18 · 2025: 29 · 2024: 35 · 2023: 39 · 2022: 42 · 2021: 65 · 2020: 77 · 2019: 92 · 2018: 95 · 2017: 72 · 2016: 64 · 2015: 75 · 2014: 94 · 2013: 112 · 2012: 120
- FWCI
- 34.22
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Symbolic Computation (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Complexity and Algorithms in Graphs
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Matrix Theory and Algorithms
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Polynomial and algebraic computation
- Keywords
- matrix multiplication, asymptotic complexity, arithmetic progressions, trilinear forms, Strassen's algorithm, matrix exponent
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review