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Michael Todd

Personal Details

First Name:Michael
Middle Name:
Last Name:Todd
Suffix:
RePEc Short-ID:pto35
[This author has chosen not to make the email address public]
https://people.orie.cornell.edu/miketodd/todd.html
Terminal Degree:1972 (from RePEc Genealogy)

Affiliation

Cornell University, School of Operations Research and Industrial Engineering

http://www.orie.cornell.edu
US, Ithaca

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Anna Fostel & Herbert E. Scarf & Michael J. Todd, 2003. "Two New Proofs of Afriat's Theorem," Cowles Foundation Discussion Papers 1415, Cowles Foundation for Research in Economics, Yale University.
  2. NESTEROV, Yurii & TODD, Michael & YE, Yinyu, 1996. "Primal-Dual Methods and Infeasibility Detectors for Nonlinear Programming Problems," LIDAM Discussion Papers CORE 1996037, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  3. NESTEROV , Yurii & TODD , Michael, 1995. "Primal-Dual Interior-Point Methods for Self-Scaled Cones," LIDAM Discussion Papers CORE 1995044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  4. NESTEROV ., Yurii E. & TODD , Michael J, 1994. "Self-Scaled Cones and Interior-Point Methods in Nonlinear Programming," LIDAM Discussion Papers CORE 1994062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  5. Freund, Robert Michael. & Todd, Michael J., 1947-, 1992. "Barrier functions and interior-point algorithms for linear programming with zero-, one-, or two-sided bounds on the variables," Working papers 3454-92., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  6. Michael J. Todd & Yinyu Ye, 1988. "A Centered Projective Algorithm for Linear Programming," Cowles Foundation Discussion Papers 861, Cowles Foundation for Research in Economics, Yale University.
  7. Freund, Robert Michael. & Roundy, Robin. & Todd, Michael J., 1947-, 1985. "Identifying the set of always-active constraints in a system of linear inequalities by a single linear program," Working papers 1674-85., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  8. TODD, Michael J., 1978. "Solving the generalized market area problem," LIDAM Reprints CORE 349, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  9. TODD, Michael J., 1978. "On the Jacobian of a function at a zero computed by a fixed point algorithm," LIDAM Reprints CORE 338, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  10. Saigal, R. & Todd, M.J., 1978. "Efficient acceleration techniques for fixed point algorithms," LIDAM Reprints CORE 344, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

Articles

  1. Marron, J.S. & Todd, Michael J. & Ahn, Jeongyoun, 2007. "Distance-Weighted Discrimination," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1267-1271, December.
  2. A. Fostel & H. Scarf & M. Todd, 2004. "Two new proofs of Afriat’s theorem," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 24(1), pages 211-219, July.
  3. Michael J. Todd, 1990. "A Dantzig-Wolfe-Like Variant of Karmarkar's Interior-Point Linear Programming Algorithm," Operations Research, INFORMS, vol. 38(6), pages 1006-1018, December.
  4. Robert G. Bland & Donald Goldfarb & Michael J. Todd, 1981. "Feature Article—The Ellipsoid Method: A Survey," Operations Research, INFORMS, vol. 29(6), pages 1039-1091, December.
  5. Robert B. Rovinsky & Christine A. Shoemaker & Michael J. Todd, 1980. "Determining Optimal Use of Resources among Regional Producers under Differing Levels of Cooperation," Operations Research, INFORMS, vol. 28(4), pages 859-866, August.
  6. Todd, Michael J., 1979. "A note on computing equilibria in economies with activity analysis models of production," Journal of Mathematical Economics, Elsevier, vol. 6(2), pages 135-144, July.
  7. Michael J. Todd, 1978. "Note--Solving the Generalized Market Area Problem," Management Science, INFORMS, vol. 24(14), pages 1549-1554, October.
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    RePEc:inm:ormoor:v:19:y:1994:i:1:p:53-67 is not listed on IDEAS
    RePEc:inm:ormoor:v:23:y:1998:i:3:p:767-768 is not listed on IDEAS

Chapters

  1. Kim-Chuan Toh & Michael J. Todd & Reha H. Tütüncü, 2012. "On the Implementation and Usage of SDPT3 – A Matlab Software Package for Semidefinite-Quadratic-Linear Programming, Version 4.0," International Series in Operations Research & Management Science, in: Miguel F. Anjos & Jean B. Lasserre (ed.), Handbook on Semidefinite, Conic and Polynomial Optimization, chapter 0, pages 715-754, Springer.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Anna Fostel & Herbert E. Scarf & Michael J. Todd, 2003. "Two New Proofs of Afriat's Theorem," Cowles Foundation Discussion Papers 1415, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. John Quah, 2014. "A test for weakly separable preferences," Economics Series Working Papers 708, University of Oxford, Department of Economics.
    2. Alan Beggs, 2021. "Afriat and arbitrage," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 9(2), pages 167-176, October.
    3. Laurens Cherchye & Bram De Rock & Vincenzo Platino, 2013. "Private versus public consumption within groups: testing the nature of goods from aggregate data," ULB Institutional Repository 2013/131703, ULB -- Universite Libre de Bruxelles.
    4. D. Wade Hands, 2014. "Paul Samuelson and Revealed Preference Theory," History of Political Economy, Duke University Press, vol. 46(1), pages 85-116, Spring.
    5. Teo Chung Piaw & Rakesh V. Vohra, 2003. "Afrait's Theorem and Negative Cycles," Discussion Papers 1377, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    6. Matthew Polisson & Ludovic Renou, 2016. "Afriat's Theorem and Samuelson's `Eternal Darkness'," Discussion Papers in Economics 16/09, Division of Economics, School of Business, University of Leicester.
    7. Alfred Galichon & John Quah, 2013. "Symposium on revealed preference analysis," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 54(3), pages 419-423, November.
    8. Santiago Sanchez-Pages, 2012. "(Don't) Make My Vote Count," Edinburgh School of Economics Discussion Paper Series 213, Edinburgh School of Economics, University of Edinburgh.
    9. Forges, Françoise & Iehlé, Vincent, 2014. "Afriat’s theorem for indivisible goods," Journal of Mathematical Economics, Elsevier, vol. 54(C), pages 1-6.
    10. John Geanakoplos, 2013. "Afriat from MaxMin," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 54(3), pages 443-448, November.
    11. Matthew Polisson, 2012. "Goods versus characteristics: dimension reduction and revealed preference," IFS Working Papers W12/02, Institute for Fiscal Studies.
    12. Ivar Ekeland & Alfred Galichon, 2013. "The Housing Problem and Revealed Preference Theory: Duality and an application," Post-Print hal-01059558, HAL.
    13. Victor H. Aguiar & Roberto Serrano, 2018. "Cardinal Revealed Preference, Price-Dependent Utility, and Consistent Binary Choice," Working Papers 2018-3, Brown University, Department of Economics.
    14. Apartsin, Yevgenia & Kannai, Yakar, 2006. "Demand properties of concavifiable preferences," Journal of Mathematical Economics, Elsevier, vol. 43(1), pages 36-55, December.
    15. Thomas Demuynck & John Rehbeck, 2023. "Computing revealed preference goodness-of-fit measures with integer programming," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 76(4), pages 1175-1195, November.
    16. Laura Blow & Richard Blundell, 2018. "A Nonparametric Revealed Preference Approach to Measuring the Value of Environmental Quality," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(3), pages 503-527, March.
    17. Matthew Polisson & John K.-H. Quah, 2013. "Revealed Preference in a Discrete Consumption Space," American Economic Journal: Microeconomics, American Economic Association, vol. 5(1), pages 28-34, February.
    18. Laurens Cherchye & Thomas Demuynck & Bram De Rock, 2012. "Revealed Preference Analysis for Convex Rationalizations on Nonlinear Budget Sets," Working Papers ECARES ECARES 2012-044, ULB -- Universite Libre de Bruxelles.
    19. Leeat Yariv & David Laibson, 2004. "Safety in Markets: An Impossibility Theorem for Dutch Books," 2004 Meeting Papers 867, Society for Economic Dynamics.
    20. Forges, Françoise & Iehlé, Vincent, 2012. "Essential Data, Budget Sets and Rationalization," MPRA Paper 36519, University Library of Munich, Germany.
    21. Francoise Forges & Enrico Minelli, 2006. "Afriat's Theorem for General Budget Sets," Working Papers ubs0609, University of Brescia, Department of Economics.
    22. Federico Echenique & Alfred Galichon, 2017. "Ordinal and cardinal solution concepts for two-sided matching," SciencePo Working papers Main hal-03261595, HAL.
    23. Sam Cosaert & Veerle Hennebel, 2023. "Parental Childcare with Process Benefits," Economica, London School of Economics and Political Science, vol. 90(357), pages 339-371, January.
    24. Sákovics, József, 2012. "Revealed cardinal preference," SIRE Discussion Papers 2012-02, Scottish Institute for Research in Economics (SIRE).
    25. Pawel Dziewulski, 2019. "Just-noticeable difference as a behavioural foundation of the critical cost-efficiency index," Working Paper Series 0519, Department of Economics, University of Sussex Business School.
    26. Halevy, Yoram & Persitz, Dotan & Zrill, Lanny, 2017. "Non-parametric bounds for non-convex preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 137(C), pages 105-112.
    27. Thomas Demuynck & Christian Seel, 2018. "Revealed Preference with Limited Consideration," American Economic Journal: Microeconomics, American Economic Association, vol. 10(1), pages 102-131, February.
    28. W D A Bryant, 2009. "General Equilibrium:Theory and Evidence," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6875.
    29. Pawel Dziewulski, 2021. "A comprehensive revealed preference approach to approximate utility maximisation," Working Paper Series 0621, Department of Economics, University of Sussex Business School.
    30. Hiroki Nishimura & Efe A. Ok & John K.-H. Quah, 2014. "A Unified Approach to Revealed Preference Theory: The Case of Rational Choice," Working Papers 201418, University of California at Riverside, Department of Economics.
    31. Sam Cosaert & Thomas Demuynck, 2015. "Revealed preference theory for finite choice sets," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 59(1), pages 169-200, May.
    32. Kohei Shiozawa, 2015. "Revealed Preference Test and Shortest Path Problem; Graph Theoretic Structure of the Rationalizability Test," Discussion Papers in Economics and Business 15-17-Rev.2, Osaka University, Graduate School of Economics, revised Aug 2016.
    33. Laurens Cherchye & Thomas Demuynck & Bram De Rock & Joshua Lanier, 2020. "Are Consumers Rational ?Shifting the Burden of Proof," Working Papers ECARES 2020-19, ULB -- Universite Libre de Bruxelles.
    34. Halevy, Yoram & Persitz, Dotan & Zrill, Lanny, 2012. "Parametric Recoverability of Preferences," Microeconomics.ca working papers yoram_halevy-2012-20, Vancouver School of Economics, revised 28 Aug 2015.
    35. Kohei Shiozawa, 2015. "Revealed Preference Test and Shortest Path Problem; Graph Theoretic Structure of the Rationalizability Test," Discussion Papers in Economics and Business 15-17, Osaka University, Graduate School of Economics.
    36. Andrés Carvajal & Rahul Deb & James Fenske & John Quah, 2014. "A nonparametric analysis of multi-product oligopolies," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 57(2), pages 253-277, October.
    37. Guy Barokas, 2020. "Identifying changing taste from demand data via golden eggs," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 54(1), pages 47-68, January.
    38. John Geanakoplos, 2013. "Afriat from MaxMin," Cowles Foundation Discussion Papers 1904, Cowles Foundation for Research in Economics, Yale University.
    39. Leeat Yariv, 2004. "Safety in Markets: An Impossibility Theorem for Dutch Books," Theory workshop papers 658612000000000072, UCLA Department of Economics.
    40. Matthew Polisson & John K.-H. Quah, 2013. "Revealed preference tests under risk and uncertainty," Discussion Papers in Economics 13/24, Division of Economics, School of Business, University of Leicester.
    41. Green, Jerry & Hojman, Daniel, 2007. "Choice, Rationality and Welfare Measurement," Working Paper Series rwp07-054, Harvard University, John F. Kennedy School of Government.
    42. Per Hjertstrand & James Swofford, 2012. "Revealed preference tests for consistency with weakly separable indirect utility," Theory and Decision, Springer, vol. 72(2), pages 245-256, February.
    43. Shiozawa, Kohei, 2016. "Revealed preference test and shortest path problem; graph theoretic structure of the rationalizability test," Journal of Mathematical Economics, Elsevier, vol. 67(C), pages 38-48.
    44. John Quah, 2012. "A revealed preference test for weakly separable preferences," Economics Series Working Papers 601, University of Oxford, Department of Economics.
    45. Aguiar, Victor H. & Serrano, Roberto, 2021. "Cardinal revealed preference: Disentangling transitivity and consistent binary choice," Journal of Mathematical Economics, Elsevier, vol. 94(C).
    46. Matthew Polisson, 2011. "Goods Versus Characteristics: Revealed Preference Procedures for Nested Models," Economics Series Working Papers 531, University of Oxford, Department of Economics.
    47. John Geanakoplos, 2013. "Afriat from MaxMin," Levine's Working Paper Archive 786969000000000746, David K. Levine.
    48. Kohei Shiozawa, 2015. "Revealed Preference Test and Shortest Path Problem; Graph Theoretic Structure of the Rationalizability Test," Discussion Papers in Economics and Business 15-17-Rev., Osaka University, Graduate School of Economics, revised Jul 2015.
    49. Satoru Fujishige & Zaifu Yang, 2012. "On Revealed Preference and Indivisibilities," Discussion Papers 12/02, Department of Economics, University of York.
    50. Christopher Chambers & Federico Echenique, 2009. "Profit maximization and supermodular technology," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 40(2), pages 173-183, August.
    51. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.
    52. Paul Oslington, 2012. "General Equilibrium: Theory and Evidence," The Economic Record, The Economic Society of Australia, vol. 88(282), pages 446-448, September.
    53. Kolesnikov, Alexander V. & Kudryavtseva, Olga V. & Nagapetyan, Tigran, 2013. "Remarks on Afriat’s theorem and the Monge–Kantorovich problem," Journal of Mathematical Economics, Elsevier, vol. 49(6), pages 501-505.

  2. NESTEROV, Yurii & TODD, Michael & YE, Yinyu, 1996. "Primal-Dual Methods and Infeasibility Detectors for Nonlinear Programming Problems," LIDAM Discussion Papers CORE 1996037, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Luo, Z-Q. & Sturm, J.F. & Zhang, S., 1998. "Conic convex programming and self-dual embedding," Econometric Institute Research Papers EI 9815, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Chris Coey & Lea Kapelevich & Juan Pablo Vielma, 2022. "Solving Natural Conic Formulations with Hypatia.jl," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2686-2699, September.
    3. Liqun Qi & Yinyu Ye, 2014. "Space tensor conic programming," Computational Optimization and Applications, Springer, vol. 59(1), pages 307-319, October.
    4. Luo, Z-Q. & Sturm, J.F. & Zhang, S., 1997. "Duality Results for Conic Convex Programming," Econometric Institute Research Papers EI 9719/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  3. NESTEROV , Yurii & TODD , Michael, 1995. "Primal-Dual Interior-Point Methods for Self-Scaled Cones," LIDAM Discussion Papers CORE 1995044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Li Yang & Bo Yu, 2013. "A homotopy method for nonlinear semidefinite programming," Computational Optimization and Applications, Springer, vol. 56(1), pages 81-96, September.
    2. Luo, Z-Q. & Sturm, J.F. & Zhang, S., 1996. "Superlinear convergence of a symmetric primal-dual path following algorithm for semidefinite programming," Econometric Institute Research Papers 9607/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. F. A. Potra & R. Sheng, 1998. "Superlinear Convergence of Interior-Point Algorithms for Semidefinite Programming," Journal of Optimization Theory and Applications, Springer, vol. 99(1), pages 103-119, October.
    4. Sturm, J.F., 2002. "Implementation of Interior Point Methods for Mixed Semidefinite and Second Order Cone Optimization Problems," Discussion Paper 2002-73, Tilburg University, Center for Economic Research.
    5. Luo, Z-Q. & Sturm, J.F. & Zhang, S., 1998. "Conic convex programming and self-dual embedding," Econometric Institute Research Papers EI 9815, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Alemseged Weldeyesus & Mathias Stolpe, 2015. "A primal-dual interior point method for large-scale free material optimization," Computational Optimization and Applications, Springer, vol. 61(2), pages 409-435, June.
    7. NESTEROV, Yu., 2006. "Nonsymmetric potential-reduction methods for general cones," LIDAM Discussion Papers CORE 2006034, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Berkelaar, A.B. & Sturm, J.F. & Zhang, S., 1996. "Polynomial Primal-Dual Cone Affine Scaling for Semidefinite Programming," Econometric Institute Research Papers EI 9667-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. A. D'Aspremont, 2003. "Interest rate model calibration using semidefinite Programming," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(3), pages 183-213.
    10. de Klerk, E. & Peng, J. & Roos, C. & Terlaky, T., 2001. "A scaled Gauss-Newton primal-dual search direction for semidefinite optimization," Other publications TiSEM 9d85401c-e9d8-45ee-be2d-2, Tilburg University, School of Economics and Management.
    11. Helmberg, C., 2002. "Semidefinite programming," European Journal of Operational Research, Elsevier, vol. 137(3), pages 461-482, March.
    12. Ali Mohammad-Nezhad & Tamás Terlaky, 2017. "A polynomial primal-dual affine scaling algorithm for symmetric conic optimization," Computational Optimization and Applications, Springer, vol. 66(3), pages 577-600, April.
    13. Sturm, J.F., 2001. "Avoiding Numerical Cancellation in the Interior Point Method for Solving Semidefinite Programs," Discussion Paper 2001-27, Tilburg University, Center for Economic Research.
    14. Arjan B. Berkelaar & Jos F. Sturm & Shuzhong Zhang, 1997. "Polynomial Primal-Dual Cone Affine Scaling for Semidefinite Programming," Tinbergen Institute Discussion Papers 97-025/4, Tinbergen Institute.
    15. Luo, Z-Q. & Sturm, J.F. & Zhang, S., 1997. "Duality Results for Conic Convex Programming," Econometric Institute Research Papers EI 9719/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Gu, G. & Zangiabadi, M. & Roos, C., 2011. "Full Nesterov-Todd step infeasible interior-point method for symmetric optimization," European Journal of Operational Research, Elsevier, vol. 214(3), pages 473-484, November.
    17. NESTEROV, Yu., 2006. "Towards nonsymmetric conic optimization," LIDAM Discussion Papers CORE 2006028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  4. NESTEROV ., Yurii E. & TODD , Michael J, 1994. "Self-Scaled Cones and Interior-Point Methods in Nonlinear Programming," LIDAM Discussion Papers CORE 1994062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Sturm, J.F., 2002. "Implementation of Interior Point Methods for Mixed Semidefinite and Second Order Cone Optimization Problems," Discussion Paper 2002-73, Tilburg University, Center for Economic Research.
    2. Alemseged Weldeyesus & Mathias Stolpe, 2015. "A primal-dual interior point method for large-scale free material optimization," Computational Optimization and Applications, Springer, vol. 61(2), pages 409-435, June.
    3. Berkelaar, A.B. & Sturm, J.F. & Zhang, S., 1996. "Polynomial Primal-Dual Cone Affine Scaling for Semidefinite Programming," Econometric Institute Research Papers EI 9667-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Terlaky, Tamas, 2001. "An easy way to teach interior-point methods," European Journal of Operational Research, Elsevier, vol. 130(1), pages 1-19, April.
    5. Helmberg, C., 2002. "Semidefinite programming," European Journal of Operational Research, Elsevier, vol. 137(3), pages 461-482, March.
    6. NESTEROV, Yu., 2006. "Constructing self-concordant barriers for convex cones," LIDAM Discussion Papers CORE 2006030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Ali Mohammad-Nezhad & Tamás Terlaky, 2017. "A polynomial primal-dual affine scaling algorithm for symmetric conic optimization," Computational Optimization and Applications, Springer, vol. 66(3), pages 577-600, April.
    8. Maziar Salahi & Renata Sotirov & Tamás Terlaky, 2004. "On self-regular IPMs," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(2), pages 209-275, December.
    9. Sturm, J.F., 2001. "Avoiding Numerical Cancellation in the Interior Point Method for Solving Semidefinite Programs," Discussion Paper 2001-27, Tilburg University, Center for Economic Research.
    10. Arjan B. Berkelaar & Jos F. Sturm & Shuzhong Zhang, 1997. "Polynomial Primal-Dual Cone Affine Scaling for Semidefinite Programming," Tinbergen Institute Discussion Papers 97-025/4, Tinbergen Institute.
    11. J.F. Sturm & S. Zhang, 1998. "On Sensitivity of Central Solutions in Semidefinite Programming," Tinbergen Institute Discussion Papers 98-040/4, Tinbergen Institute.
    12. NESTEROV, Yu., 2006. "Towards nonsymmetric conic optimization," LIDAM Discussion Papers CORE 2006028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  5. Freund, Robert Michael. & Todd, Michael J., 1947-, 1992. "Barrier functions and interior-point algorithms for linear programming with zero-, one-, or two-sided bounds on the variables," Working papers 3454-92., Massachusetts Institute of Technology (MIT), Sloan School of Management.

    Cited by:

    1. Ordónez, Fernando & Freund, Robert M., 2003. "Computational Experience and the Explanatory Value of Condition Numbers for Linear Optimization," Working papers 4337-02, Massachusetts Institute of Technology (MIT), Sloan School of Management.

  6. Michael J. Todd & Yinyu Ye, 1988. "A Centered Projective Algorithm for Linear Programming," Cowles Foundation Discussion Papers 861, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Freund, Robert Michael., 1989. "A potential-function reduction algorithm for solving a linear program directly from an infeasible "warm start"," Working papers 3079-89., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Bertsimas, Dimitris. & Luo, Xiaodong., 1993. "On the worst case complexity of potential reduction algorithms for linear programming," Working papers 3558-93., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    3. Bosch, Ronald J. & Ye, Yinyu & Woodworth, George G., 1995. "A convergent algorithm for quantile regression with smoothing splines," Computational Statistics & Data Analysis, Elsevier, vol. 19(6), pages 613-630, June.

  7. Freund, Robert Michael. & Roundy, Robin. & Todd, Michael J., 1947-, 1985. "Identifying the set of always-active constraints in a system of linear inequalities by a single linear program," Working papers 1674-85., Massachusetts Institute of Technology (MIT), Sloan School of Management.

    Cited by:

    1. Toubia, Olivier & Simester, Duncan & Hauser, John & Dahan, Ely, 2003. "Fast Polyhedral Adaptive Conjoint Estimation," Working papers 4279-02, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Dritan Nace & James B. Orlin, 2007. "Lexicographically Minimum and Maximum Load Linear Programming Problems," Operations Research, INFORMS, vol. 55(1), pages 182-187, February.
    3. Georgios Saharidis & Marianthi Ierapetritou, 2013. "Speed-up Benders decomposition using maximum density cut (MDC) generation," Annals of Operations Research, Springer, vol. 210(1), pages 101-123, November.
    4. Bharat Adsul & Jugal Garg & Ruta Mehta & Milind Sohoni & Bernhard von Stengel, 2021. "Fast Algorithms for Rank-1 Bimatrix Games," Operations Research, INFORMS, vol. 69(2), pages 613-631, March.
    5. Gelareh, Shahin & Neamatian Monemi, Rahimeh & Nickel, Stefan, 2015. "Multi-period hub location problems in transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 67-94.

  8. Saigal, R. & Todd, M.J., 1978. "Efficient acceleration techniques for fixed point algorithms," LIDAM Reprints CORE 344, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. R. Saigal, 1977. "On Piecewise Linear Approximations to Smooth Mappings," Discussion Papers 311, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    2. Galadí, J.A. & Soler-Toscano, F. & Langa, J.A., 2022. "Model transform and local parameters. Application to instantaneous attractors," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).

Articles

  1. Marron, J.S. & Todd, Michael J. & Ahn, Jeongyoun, 2007. "Distance-Weighted Discrimination," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1267-1271, December.

    Cited by:

    1. Jang, Hyun Jung & Shin, Seung Jun & Artemiou, Andreas, 2023. "Principal weighted least square support vector machine: An online dimension-reduction tool for binary classification," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    2. Makoto Aoshima & Kazuyoshi Yata, 2014. "A distance-based, misclassification rate adjusted classifier for multiclass, high-dimensional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(5), pages 983-1010, October.
    3. Xiaosun Lu & J. S. Marron & Perry Haaland, 2014. "Object-Oriented Data Analysis of Cell Images," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 548-559, June.
    4. Makoto Aoshima & Kazuyoshi Yata, 2019. "High-Dimensional Quadratic Classifiers in Non-sparse Settings," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 663-682, September.
    5. Hayley Randall & Andreas Artemiou & Xingye Qiao, 2021. "Sufficient dimension reduction based on distance‐weighted discrimination," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1186-1211, December.
    6. Sudhir Varma, 2020. "Blind estimation and correction of microarray batch effect," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-15, April.
    7. Jung, Sungkyu, 2018. "Continuum directions for supervised dimension reduction," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 27-43.
    8. Bolivar-Cime, A. & Marron, J.S., 2013. "Comparison of binary discrimination methods for high dimension low sample size data," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 108-121.
    9. Makoto Aoshima & Kazuyoshi Yata, 2019. "Distance-based classifier by data transformation for high-dimension, strongly spiked eigenvalue models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(3), pages 473-503, June.
    10. Sungkyu Jung & Xingye Qiao, 2014. "A statistical approach to set classification by feature selection with applications to classification of histopathology images," Biometrics, The International Biometric Society, vol. 70(3), pages 536-545, September.
    11. Ishii, Aki & Yata, Kazuyoshi & Aoshima, Makoto, 2022. "Geometric classifiers for high-dimensional noisy data," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    12. Marron, J.S., 2017. "Big Data in context and robustness against heterogeneity," Econometrics and Statistics, Elsevier, vol. 2(C), pages 73-80.
    13. Anil K. Ghosh & Munmun Biswas, 2016. "Distribution-free high-dimensional two-sample tests based on discriminating hyperplanes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 525-547, September.
    14. Yugo Nakayama & Kazuyoshi Yata & Makoto Aoshima, 2020. "Bias-corrected support vector machine with Gaussian kernel in high-dimension, low-sample-size settings," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(5), pages 1257-1286, October.
    15. Niladri Roy Chowdhury & Dianne Cook & Heike Hofmann & Mahbubul Majumder & Eun-Kyung Lee & Amy Toth, 2015. "Using visual statistical inference to better understand random class separations in high dimension, low sample size data," Computational Statistics, Springer, vol. 30(2), pages 293-316, June.
    16. Giuliodori, Andrea & Lillo Rodríguez, Rosa Elvira & Peña, Daniel, 2009. "Clustering and classifying images with local and global variability," DES - Working Papers. Statistics and Econometrics. WS ws090101, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Tianxiao Sun & Ion Necoara & Quoc Tran-Dinh, 2020. "Composite convex optimization with global and local inexact oracles," Computational Optimization and Applications, Springer, vol. 76(1), pages 69-124, May.

  2. A. Fostel & H. Scarf & M. Todd, 2004. "Two new proofs of Afriat’s theorem," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 24(1), pages 211-219, July.
    See citations under working paper version above.
  3. Michael J. Todd, 1990. "A Dantzig-Wolfe-Like Variant of Karmarkar's Interior-Point Linear Programming Algorithm," Operations Research, INFORMS, vol. 38(6), pages 1006-1018, December.

    Cited by:

    1. Holder, A.G. & Sturm, J.F. & Zhang, S., 1998. "Analytic central path, sensitivity analysis and parametric linear programming," Econometric Institute Research Papers EI 9801, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Zhang, S., 1998. "Global error bounds for convex conic problems," Econometric Institute Research Papers EI 9830, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. A.G. Holder & J.F. Sturm & S. Zhang, 1998. "Analytic Central Path, Sensitivity Analysis and Parametric Linear Programming," Tinbergen Institute Discussion Papers 98-003/4, Tinbergen Institute.
    4. J.F. Sturm & S. Zhang, 1998. "On Sensitivity of Central Solutions in Semidefinite Programming," Tinbergen Institute Discussion Papers 98-040/4, Tinbergen Institute.
    5. Li-Zhi Liao, 2014. "A Study of the Dual Affine Scaling Continuous Trajectories for Linear Programming," Journal of Optimization Theory and Applications, Springer, vol. 163(2), pages 548-568, November.

  4. Robert G. Bland & Donald Goldfarb & Michael J. Todd, 1981. "Feature Article—The Ellipsoid Method: A Survey," Operations Research, INFORMS, vol. 29(6), pages 1039-1091, December.

    Cited by:

    1. Maxime C. Cohen & Ilan Lobel & Renato Paes Leme, 2020. "Feature-Based Dynamic Pricing," Management Science, INFORMS, vol. 66(11), pages 4921-4943, November.
    2. Yaguang Yang, 2013. "A Polynomial Arc-Search Interior-Point Algorithm for Linear Programming," Journal of Optimization Theory and Applications, Springer, vol. 158(3), pages 859-873, September.
    3. Paul Karaenke & Martin Bichler & Stefan Minner, 2019. "Coordination Is Hard: Electronic Auction Mechanisms for Increased Efficiency in Transportation Logistics," Management Science, INFORMS, vol. 65(12), pages 5884-5900, December.
    4. Tanaka, Masato & Matsui, Tomomi, 2022. "Pseudo polynomial size LP formulation for calculating the least core value of weighted voting games," Mathematical Social Sciences, Elsevier, vol. 115(C), pages 47-51.
    5. V. Balakrishnan & R. L. Kashyap, 1999. "Robust Stability and Performance Analysis of Uncertain Systems Using Linear Matrix Inequalities," Journal of Optimization Theory and Applications, Springer, vol. 100(3), pages 457-478, March.
    6. K. A. Ariyawansa & P. L. Jiang, 2000. "On Complexity of the Translational-Cut Algorithm for Convex Minimax Problems," Journal of Optimization Theory and Applications, Springer, vol. 107(2), pages 223-243, November.
    7. Simone A. Rocha & Thiago G. Mattos & Rodrigo T. N. Cardoso & Eduardo G. Silveira, 2022. "Applying Artificial Neural Networks and Nonlinear Optimization Techniques to Fault Location in Transmission Lines—Statistical Analysis," Energies, MDPI, vol. 15(11), pages 1-24, June.
    8. Zhang, Yufeng & Khani, Alireza, 2019. "An algorithm for reliable shortest path problem with travel time correlations," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 92-113.

  5. Robert B. Rovinsky & Christine A. Shoemaker & Michael J. Todd, 1980. "Determining Optimal Use of Resources among Regional Producers under Differing Levels of Cooperation," Operations Research, INFORMS, vol. 28(4), pages 859-866, August.

    Cited by:

    1. Jang, Joonkyung, 1992. "A spatial equilibrium analysis of the impact of transportation costs and policy changes on the export of U.S. beef and feed grains," ISU General Staff Papers 1992010108000017632, Iowa State University, Department of Economics.

  6. Todd, Michael J., 1979. "A note on computing equilibria in economies with activity analysis models of production," Journal of Mathematical Economics, Elsevier, vol. 6(2), pages 135-144, July.

    Cited by:

    1. Galeazzo Impicciatore & Luca Panaccione, 2007. "A Note on Equilibrium with Capital Goods, Storage and Production," Working Papers in Public Economics 99, University of Rome La Sapienza, Department of Economics and Law.
    2. Galeazzo Impicciatore & Luca Panaccione & Francesco Ruscitti, 2012. "Walras’ theory of capital formation: an intertemporal equilibrium reformulation," Journal of Economics, Springer, vol. 106(2), pages 99-118, June.
    3. Galeazzo Impicciatore & Luca Panaccione & Francesco Ruscitti, 2009. "Intertemporal Equilibrium and Walras' Theory of Capital: a Projection Based Approach," Working Papers in Public Economics 121, University of Rome La Sapienza, Department of Economics and Law.

Chapters

  1. Kim-Chuan Toh & Michael J. Todd & Reha H. Tütüncü, 2012. "On the Implementation and Usage of SDPT3 – A Matlab Software Package for Semidefinite-Quadratic-Linear Programming, Version 4.0," International Series in Operations Research & Management Science, in: Miguel F. Anjos & Jean B. Lasserre (ed.), Handbook on Semidefinite, Conic and Polynomial Optimization, chapter 0, pages 715-754, Springer.

    Cited by:

    1. Kurt M. Anstreicher, 2018. "Maximum-entropy sampling and the Boolean quadric polytope," Journal of Global Optimization, Springer, vol. 72(4), pages 603-618, December.
    2. Sungwoo Park & Dianne P. O’Leary, 2015. "A Polynomial Time Constraint-Reduced Algorithm for Semidefinite Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 166(2), pages 558-571, August.
    3. Dawen Yan & Xiaohui Zhang & Mingzheng Wang, 2021. "A robust bank asset allocation model integrating credit-rating migration risk and capital adequacy ratio regulations," Annals of Operations Research, Springer, vol. 299(1), pages 659-710, April.
    4. Kristijan Cafuta, 2019. "Sums of Hermitian squares decomposition of non-commutative polynomials in non-symmetric variables using NCSOStools," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(2), pages 397-413, June.
    5. Kurt M. Anstreicher, 2020. "Efficient Solution of Maximum-Entropy Sampling Problems," Operations Research, INFORMS, vol. 68(6), pages 1826-1835, November.
    6. He, Qie & Zhang, Xiaochen & Nip, Kameng, 2017. "Speed optimization over a path with heterogeneous arc costs," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 198-214.

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