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A new polynomial-time algorithm for linear programming
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Cites
Linear Programming and Extensions
Dantzig, G. (1963) · RAND Corporation eBooks · doi:10.7249/r366 · Cited by 5,755
Linear Programming and Extensions
Dantzig, G. (1963) · Princeton University Press eBooks · doi:10.1515/9781400884179 · Cited by 2,713
The ellipsoid method and its consequences in combinatorial optimization
Grötschel, M., Lovász, L., & Schrijver, A. (1981) · Combinatorica · doi:10.1007/bf02579273 · Cited by 2,011
Polynomial algorithms in linear programming
Khachiyan, L. G. (1980) · USSR Computational Mathematics and Mathematical Physics · doi:10.1016/0041-5553(80)90061-0 · Cited by 1,992
Coxeter, H. S. M. (1969) · Cited by 1,582
HOW GOOD IS THE SIMPLEX ALGORITHM
Klee, V. L., & Minty, G. J. (1970) · Cited by 769
Petersen, G. M., & Coxeter, H. S. M. (1961) · The American Mathematical Monthly · doi:10.2307/2311833 · Cited by 540
Cited by
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
The Earth Mover's Distance as a Metric for Image Retrieval
Rubner, Y., Tomasi, C., & Guibas, L. J. (2000) · International Journal of Computer Vision · doi:10.1023/a:1026543900054 · Cited by 4,568
Learnability and the Vapnik-Chervonenkis dimension
Blumer, A., Ehrenfeucht, A., Haussler, D., & Warmuth, M. K. (1989) · Journal of the ACM · doi:10.1145/76359.76371 · Cited by 1,839
Convex position estimation in wireless sensor networks
Doherty, L., pister, K. S. J., & El Ghaoui, L. (2002) · Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213) · doi:10.1109/infcom.2001.916662 · Cited by 1,632
On the Implementation of a Primal-Dual Interior Point Method
Mehrotra, S. (1992) · SIAM Journal on Optimization · doi:10.1137/0802028 · Cited by 1,613
Predictive Control for Linear and Hybrid Systems
Borrelli, F., Bemporad, A., & Morari, M. (2017) · Cambridge University Press eBooks · doi:10.1017/9781139061759 · Cited by 1,443
Engineering Optimization: Theory and Practice
Rao, S. S. (2009) · Wiley eBooks · doi:10.1002/9780470549124 · Cited by 1,254
Artificial Intelligence: A New Synthesis
(1998) · Elsevier eBooks · doi:10.1016/c2009-0-27773-7 · Cited by 1,163
Disciplined Convex Programming
Grant, M., Boyd, S., & Ye, Y. (2006) · Nonconvex Optimization and Its Applications · doi:10.1007/0-387-30528-9_7 · Cited by 1,026
Multiple Object Tracking Using K-Shortest Paths Optimization
Berclaz, J., Fleuret, F., Turetken, E., & Fua, P. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.21 · Cited by 1,015
Practical Bilevel Optimization
Bard, J. F. (1998) · Nonconvex Optimization and Its Applications · doi:10.1007/978-1-4757-2836-1 · Cited by 930
Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization
Alizadeh, F. (1995) · SIAM Journal on Optimization · doi:10.1137/0805002 · Cited by 892
Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time
Spielman, D. A., & Teng, S.-H. (2004) · Journal of the ACM · doi:10.1145/990308.990310 · Cited by 825
ViNEYard: Virtual Network Embedding Algorithms With Coordinated Node and Link Mapping
Chowdhury, M., Rahman, M. R., & Boutaba, R. (2012) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2011.2159308 · Cited by 818
Andersen, E. D., & Andersen, K. D. (2000) · Applied Optimization · doi:10.1007/978-1-4757-3216-0_8 · Cited by 766
Interior Methods for Nonlinear Optimization
Forsgren, A., Gill, P. E., & Wright, M. H. (2002) · SIAM Review · doi:10.1137/s0036144502414942 · Cited by 699
Settling the complexity of computing two-player Nash equilibria
Chen, X., Deng, X., & Teng, S.-H. (2009) · Journal of the ACM · doi:10.1145/1516512.1516516 · Cited by 560
Optimal power flow: a bibliographic survey I: Formulations and deterministic methods
Frank, S., Steponavice, I., & Rebennack, S. (2012) · Energy Systems · doi:10.1007/s12667-012-0056-y · Cited by 554
Constraint propagation with interval labels
Davis, E. (1987) · Artificial Intelligence · doi:10.1016/0004-3702(87)90091-9 · Cited by 531
On the convergence of the coordinate descent method for convex differentiable minimization
Luo, Z. Q., & Tseng, P. (1992) · Journal of Optimization Theory and Applications · doi:10.1007/bf00939948 · Cited by 502
Linear Matrix Inequalities In System And Control Theory
Yaz, E. E. (1998) · Proceedings of the IEEE · doi:10.1109/jproc.1998.735454 · Cited by 428
Some applications of Laplace eigenvalues of graphs
Mohar, B. (1997) · Graph Symmetry · doi:10.1007/978-94-015-8937-6_6 · Cited by 422
An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison
Ling, H., & Okada, K. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1058 · Cited by 414
A general lower bound on the number of examples needed for learning
Ehrenfeucht, A., Haussler, D., Kearns, M., & Valiant, L. (1989) · Information and Computation · doi:10.1016/0890-5401(89)90002-3 · Cited by 403
Energy Management Optimization in a Battery/Supercapacitor Hybrid Energy Storage System
Choi, M.-E., Kim, S.-W., & Seo, S.-W. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2011.2164816 · Cited by 389
Solving Real-World Linear Programs: A Decade and More of Progress
Bixby, R. E. (2002) · Operations Research · doi:10.1287/opre.50.1.3.17780 · Cited by 386
Interior point methods 25 years later
Gondzio, J. (2012) · European Journal of Operational Research · doi:10.1016/j.ejor.2011.09.017 · Cited by 377
Moore, C., & Mertens, S. (2011) · doi:10.1093/acprof:oso/9780199233212.001.0001 · Cited by 347
Fast $\ell_{1}$-Minimization Algorithms for Robust Face Recognition
Yang, A. Y., Zhou, Z., Balasubramanian, A. G., Sastry, S. S., & Ma, Y. (2013) · IEEE Transactions on Image Processing · doi:10.1109/tip.2013.2262292 · Cited by 341
A subexponential bound for linear programming
Matoušek, J., Sharir, M., & Welzl, E. (1996) · Algorithmica · doi:10.1007/bf01940877 · Cited by 300
Perceptual Metrics for Image Database Navigation
Rubner, Y., & Tomasi, C. (2001) · Springer eBooks · doi:10.1007/978-1-4757-3343-3 · Cited by 296
Solving Large-Scale Sparse Semidefinite Programs for Combinatorial Optimization
Benson, S. J., Ye, Y., & Zhang, X. (2000) · SIAM Journal on Optimization · doi:10.1137/s1052623497328008 · Cited by 276
Malyuta, D., Reynolds, T. P., Szmuk, M., Lew, T., Bonalli, R., Pavone, M., & Açıkmeşe, B. (2022) · IEEE Control Systems · doi:10.1109/mcs.2022.3187542 · Cited by 259
Efficient algorithms for geometric optimization
Agarwal, P. K., & Sharir, M. (1998) · ACM Computing Surveys · doi:10.1145/299917.299918 · Cited by 257
Efficient Algorithms for Capacitated Cloudlet Placements
Xu, Z., Liang, W., Xu, W., Jia, M., & Guo, S. (2016) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2015.2510638 · Cited by 256
Zohdy, I. H., & Rakha, H. A. (2016) · Journal of Intelligent Transportation Systems · doi:10.1080/15472450.2014.889918 · Cited by 182
Rossi, F., Zhang, R., Hindy, Y., & Pavone, M. (2018) · Autonomous Robots · doi:10.1007/s10514-018-9750-5 · Cited by 153
Investigating the Performance of Pull-Based Dynamic Adaptive Streaming in NDN
Rainer, B., Posch, D., & Hellwagner, H. (2016) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2016.2577365 · Cited by 62
Vanderbei, R. J. (2015) · Encyclopedia of Applied and Computational Mathematics · doi:10.1007/978-3-540-70529-1_419 · Cited by 27
Metadata
- Authors
- Karmarkar, N.
- Venue
- Combinatorica
- Published
- 1984-12
- Volume
- 4
- Issue
- 4
- Pages
- 373-395
- ISSN
- 0209-9683 (ISSN-L)
- 1439-6912
- OpenAlex
- W2611147814
- Cited by
- 4,794
- References
- 7
- FWCI
- 58.16
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
