Inferring Sparse Preference Lists from Partial Information
Published Online:7 Oct 2020https://doi.org/10.1287/stsy.2019.0060
References
- (2008) Parimutuel betting on permutations. Papadimitriou C, Zhang S, eds. WINE 2008: Internet and Network Economics. (Springer, Berlin), 126–137.Google Scholar
- (2012) The multiplicative weights update method: A meta-algorithm and applications. Theory of Computing. 8(6):121–164.Google Scholar
- (1999) Testing the multinomial logit model. Working paper, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin.Google Scholar
- (1973) Structure of passenger travel demand models. PhD thesis, Department of Civil Engineering, Massachusetts Institute of Technology, Cambridge, MA.Google Scholar
- (1985) Discrete Choice Analysis: Theory and Application to Travel Demand (CMIT Press, Cambridge, MA).Google Scholar
- (1979) Exponential models for directional data. Ann. Statist. 7(6):1162–1178.Google Scholar
- (2008) Combining geometry and combinatorics: A unified approach to sparse signal recovery. Proc. 46th Annual Allerton Conf. on Communication, Control, and Computing (IEEE, New York), 798–805.Google Scholar
- (1946) Tres observaciones sobre el algebra lineal. Univ. Nac. Tucuman Rev. Ser. A 5:147–151.Google Scholar
- (1980) The effect of fuel economy standards on the u.s. automotive market: An hedonic demand analysis. Transporation Res. Part A General 14(5–6):367–378.Google Scholar
- (1953) Some statistical methods in taste testing and quality evaluation. Biometrics 9:22–38.Google Scholar
- (2006) Quantitative robust uncertainty principles and optimally sparse decompositions. Foundations Comput. Math. 6(2):227–254.Google Scholar
- (2005) Decoding by linear programming. IEEE Trans. Inform. Theory 51(12):4203–4215.Google Scholar
- (2006a) Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inform. Theory 52(2):489–509.Google Scholar
- (2006b) Stable signal recovery from incomplete and inaccurate measurements. Commun. Pure Appl. Math. 59(8):1207–1223.Google Scholar
- (1980) Measuring the societal impacts of automobile downsizing. Transporation Res. Part A General 14(5–6):423–434.Google Scholar
- (2006) Combinatorial algorithms for compressed sensing. Lecture Notes Comput. Sci. 4056:280.Google Scholar
- (1976) Exponential models, maximum likelihood estimation, and the haar condition. J. Amer. Statist. Assoc. 71:737–745.Google Scholar
- (1960) Review of r. d. luce, ‘individual choice behavior: A theoretical analysis’. Amer. Econom. Rev. 50:186–188.Google Scholar
- (1988) Group Representations in Probability and Statistics (Institute of Mathematical Statistics, Hayward, CA).Google Scholar
- (1989) A generalization of spectral analysis with application to ranked data. Ann. Statist. 17(3):949–979.Google Scholar
- (2006) Compressed sensing. IEEE Trans. Inform. Theory 52(4):1289–1306.Google Scholar
- (2009) A data-driven approach to modeling choice. Bengio Y, Schuurmans D, Lafferty JD, Williams CKI, Culotta A, eds. Neural Information Processing Systems (Curran Associates, Inc., Red Hook, NY), 504–512.Google Scholar
- (2013) A nonparametric approach to modeling choice with limited data. Management Sci. 59(2):305–322.Link, Google Scholar
- (1983) Paradoxes of preferential voting. Math. Magazine 56(4):207–214.Google Scholar
- (1962) Low-density parity-check codes.IEEE Trans. Inform. Theory 8(1):21–28.Google Scholar
- (2007) One sketch for all: Fast algorithms for compressed sensing. Proc. 39th Annu. ACM Sympos. on Theory of Computing (ACM, New York), 237–246.Google Scholar
- (1983) A logit model of brand choice calibrated on scanner data. Marketing Sci. 2(3):203–238.Link, Google Scholar
- (1993) Semiparametric estimation of a work-trip mode choice model. J. Econometrics 58:49–70.Google Scholar
- (2011) Nonparametric choice modeling: Applications to operations management. PhD thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA.Google Scholar
- (2014). Assortment optimization under general choice. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2512831.Google Scholar
- (2008) Inferring rankings under constrained sensing. Koller D, Schuurmans D, Bengio Y, Bottou L, eds. Advances in Neural Information Processing Systems 21 (Curran Associates, Inc., Red Hook, NY), 753–760.Google Scholar
- (2011) Inferring rankings under constrained sensing. IEEE Trans. Inform. Theory 57(11):7288–7306.Google Scholar
- (2013) Revisiting Frank-Wolfe: Projection-free sparse convex optimization. Dasgupta S, McAllester D, eds. Proc. of the 30th Internat. Conf. on Machine Learn. (Proceedings of Machine Learning Research, Atlanta, Georgia), 427–435Google Scholar
- (2005) Supervised ordering-an empirical survey. Proc. 5th IEEE Internat. Conf. on Data Mining (ICDM’05) (IEEE, New York), 673–676.Google Scholar
- (1936) On distributions admitting a sufficient statistic. Trans. Amer. Math. Soc. 39(3):399–409.Google Scholar
- (2001) Improved low-density parity-check codes using irregular graphs. IEEE Trans. Inform. Theory 47(2):585–598.Google Scholar
- (1959) Individual Choice Behavior: A Theoretical Analysis (Wiley, New York).Google Scholar
- (1999) On the relationship between inventory costs and variety benefits in retail assortments. Management Sci. 45(11):1496–1509.Link, Google Scholar
- (1995) Analyzing and Modeling Rank Data (Chapman & Hall/CRC, New York).Google Scholar
- (1959) Binary Choice Constraints on Random Utility Indicators (Cowles Foundation Discussion Papers, New Haven, CT).Google Scholar
- (1972) Economic Theory of Teams (Yale University Press, New Haven, CT).Google Scholar
- (1973) Conditional logit analysis of qualitative choice behavior. Zarembka P, ed. Frontiers in Econometrics (Academic Press, New York), 105–142.Google Scholar
- (1981) Econometric models of probabilistic choice. Manski CF, McFadden D, eds. Structural Analysis of Discrete Data with Econometric Applications (MIT Press, Cambridge, MA), 198–272.Google Scholar
- (2000) Disaggregate Behavioral Travel Demands Rum Side. 9th Internat. Conf. on Travel Behaviour Res. (Queensland, Australia), 38.Google Scholar
- (2000) Mixed MNL models for discrete response. J. Appl. Econometrics 15(5):447–470.Google Scholar
- (2002) Certain topics in telegraph transmission theory. Proc. IEEE 90(2):280–305.Google Scholar
- (1975) The analysis of permutations. Appl. Statist. 24(2):193–202.Google Scholar
- (1995) Fast approximation algorithms for fractional packing and covering problems. Math. of Oper. Res. 20(2):257–301.Google Scholar
- (1960) Polynomial codes over certain finite fields. J. Soc. Ind. Appl. Math. 8(2):300–304.Google Scholar
- (1949) Communication in the presence of noise. Proc. IRE 37(1):10–21.Google Scholar
- (1996) Expander codes. IEEE Trans. Inform. Theory 42:1710–1722.Google Scholar
- (1927) A law of comparative judgement. Psychol. Rev. 34:237–286.Google Scholar
- (2004) Greed is good: Algorithmic results for sparse approximation. IEEE Trans. Inform. Theory 50(10):2231–2242.Google Scholar
- (2006) Just relax: Convex programming methods for identifying sparse signals in noise. IEEE Trans. Inform. Theory 52(3):1030–1051.Google Scholar
- (1953) A certain zero-sum two-person game equivalent to the optimal assignment problem. Contributions to the Theory of Games. 2:5–12.Google Scholar
- (2008) Graphical models, exponential families, and variational inference. Foundations Trends Machine Learning 1(1–2):1–305.Google Scholar
- (1977) The relationship between luce’s choice axiom, thurstone’s theory of comparative judgment, and the double exponential distribution. J. Math. Psychol. 15(2):109–144.Google Scholar

