Learning Preferences with Side Information
Published Online:8 May 2019https://doi.org/10.1287/mnsc.2018.3092
References
- (2005) Modeling and multiway analysis of chatroom tensors. Kantor P, Muresan G, Roberts F, Zeng D, Wang F-Y, Chen H, Merkle R, eds. IEEE Internat. Conf. Intelligence Security Informatics Proc. (Springer, Berlin), 256–268.Crossref, Google Scholar
- (2007) Fast computation of low-rank matrix approximations. J. ACM 54(2):Article 9.Crossref, Google Scholar
- (2005) Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowledge Data Engrg. 17(6):734–749.Crossref, Google Scholar
- (2003) E-customization. J. Marketing Res. 40(2):131–145.Crossref, Google Scholar
- (2000) Internet recommendation systems. J. Marketing Res. 37(3):363–375.Crossref, Google Scholar
- (2014) Fast multivariate spatio-temporal analysis via low rank tensor learning. Ghahramani Z, Welling M, Cortes C, Lawrence ND, Weinberger KQ, eds. Advances in Neural Information Processing Systems, vol. 27 (Curran Associates, Red Hook, NY), 3491–3499.Google Scholar
- (2014) Music discovery at Spotify. Presentation, Machine Learning Conference, April 14, Helen Mills Event Center, New York.Google Scholar
- (1995) Using linear algebra for intelligent information retrieval. SIAM Rev. 37(4):573–595.Crossref, Google Scholar
- (2015) Optimization in online content recommendation services: Beyond click-through rates. Manufacturing Service Oper. Management 18(1):15–33.Link, Google Scholar
- (2008) Recommendation systems with purchase data. J. Marketing Res. 45(1):77–93.Crossref, Google Scholar
- (2011) Tight oracle inequalities for low-rank matrix recovery from a minimal number of noisy random measurements. IEEE Trans. Inform. Theory 57(4):2342–2359.Crossref, Google Scholar
- (2010) The power of convex relaxation: Near-optimal matrix completion. IEEE Trans. Inform. Theory 56(5):2053–2080.Crossref, Google Scholar
- (1970) Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition. Psychometrika 35(3):283–319.Crossref, Google Scholar
- (1966) The scree test for the number of factors. Multivariate Behav. Res. 1(2):245–276.Crossref, Google Scholar
- (2014) Matrix estimation by universal singular value thresholding. Ann. Statist. 43(1):177–214.Crossref, Google Scholar
- (2015) Matrix completion with noisy side information. Cortes C, Lawrence ND, Lee DD, Sugiyama M, Garnett R, eds. Advances in Neural Information Processing Systems, vol. 28 (Curran Associates, Red Hook, NY), 3429–3437.Google Scholar
- (2009) My mobile music: An adaptive personalization system for digital audio players. Marketing Sci. 28(1):52–68.Link, Google Scholar
- (2016) Optimization of recommender systems based on inventory. Production Oper. Management 25(4):593–608.Crossref, Google Scholar
- (2009) Blockbuster culture’s next rise or fall: The impact of recommender systems on sales diversity. Management Sci. 55(5):697–712.Link, Google Scholar
- (2011) Tensor completion and low-n-rank tensor recovery via convex optimization. Inverse Problems 27(2):Article 025010.Crossref, Google Scholar
- (2008) Shopbot 2.0: Integrating recommendations and promotions with comparison shopping. Decision Support Systems 46(1):61–69.Crossref, Google Scholar
- (2014) The optimal hard threshold for singular values is 4/√ 3. IEEE Trans. Inform. Theory 60(8):5040–5053.Crossref, Google Scholar
- (2012) Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content. Marketing Sci. 31(3):493–520.Link, Google Scholar
- (1992) Using collaborative filtering to weave an information tapestry. Comm. ACM 35(12):61–70.Crossref, Google Scholar
- (2015) How many products does Amazon sell? Export-x (December 11), https://export-x.com/2015/12/11/how-many-products-does-amazon-sell-2015/.Google Scholar
- (2011) Recovering low-rank matrices from few coefficients in any basis. IEEE Trans. Inform. Theory 57(3):1548–1566.Crossref, Google Scholar
- (1987) A simultaneous approach to market segmentation and market structuring. J. Marketing Res. 24(2):139–153.Crossref, Google Scholar
- (2015) Amazon sold 5 billion items in 2014. Fast Company (January 6), http://www.fastcompany.com/3040445/fast-feed/amazon-sold-5-billion-items-in-2014.Google Scholar
- (1994) N-way principal component analysis theory, algorithms and applications. Chemometrics Intelligent Laboratory Systems 25(1):1–23.Crossref, Google Scholar
- (2007) Model averaging and dimension selection for the singular value decomposition. J. Amer. Statist. Assoc. 102(478):674–685.Crossref, Google Scholar
- (2008) Recommended for you: The impact of profit incentives on the relevance of online recommendations. ICIS 2008 Proc. (Association for Information Systems, Atlanta), Paper 31.Google Scholar
- (2015) Provable models for robust low-rank tensor completion. Pacific J. Optim. 11(2):339–364.Google Scholar
- (2016) Model-based purchase predictions for large assortments. Marketing Sci. 35(3):389–404.Link, Google Scholar
- (2013) Provable inductive matrix completion. Working paper, University of Texas at Austin, Austin.Google Scholar
- (2014) Provable tensor factorization with missing data. Ghahramani Z, Welling M, Cortes C, Lawrence ND, Weinberger KQ, eds. Advances in Neural Information Processing Systems, vol. 27 (Curran Associates, Red Hook, NY), 1431–1439.Google Scholar
- (2010) Matrix completion from a few entries. IEEE Trans. Inform. Theory 56(6):2980–2998.Crossref, Google Scholar
- (1999) Authoritative sources in a hyperlinked environment. J. ACM 46(5):604–632.Crossref, Google Scholar
- (2009) Tensor decompositions and applications. SIAM Rev. 51(3):455–500.Crossref, Google Scholar
- (2011) Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion. Ann. Statist. 39(5):2302–2329.Crossref, Google Scholar
- (2009) Matrix factorization techniques for recommender systems. Computer 42(8):30–37.Crossref, Google Scholar
- (1998) Lanczos bidiagonalization with partial reorthogonalization. DAIMI Rep. Ser. 27(537).Google Scholar
- (2007) The link-prediction problem for social networks. J. Amer. Soc. Inform. Sci. Tech. 58(7):1019–1031.Crossref, Google Scholar
- (2003) Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Comput. 7(1):76–80.Crossref, Google Scholar
- (2013) Tensor completion for estimating missing values in visual data. IEEE Trans. Pattern Anal. Machine Intelligence 35(1):208–220.Crossref, Google Scholar
- (2014) Generalized higher-order orthogonal iteration for tensor decomposition and completion. Ghahramani Z, Welling M, Cortes C, Lawrence ND, Weinberger KQ, eds. Advances in Neural Information Processing Systems, vol. 27 (Curran Associates, Red Hook, NY), 1763–1771.Google Scholar
- (1967) Distribution of eigenvalues for some sets of random matrices. Math. USSR-Sbornik 1(4):457–483.Crossref, Google Scholar
- (2011) Applications of tensor (multiway array) factorizations and decompositions in data mining. Wiley Interdisciplinary Rev.: Data Mining Knowledge Discovery 1(1):24–40.Crossref, Google Scholar
- (2013) Square deal: Lower bounds and improved relaxations for tensor recovery. Working paper, Columbia University, New York.Google Scholar
- (2008) Challenges and opportunities in high-dimensional choice data analyses. Marketing Lett. 19(3–4):201–213.Crossref, Google Scholar
- (2000) A Bayesian computer vision system for modeling human interactions. IEEE Trans. Pattern Anal. Machine Intelligence 22(8):831–843.Crossref, Google Scholar
- (2009) Bi-cross-validation of the SVD and the nonnegative matrix factorization. Ann. Appl. Statist. 3(2):564–594.Crossref, Google Scholar
- (1998) Latent semantic indexing: A probabilistic analysis. Proc. 17th ACM SIGACT-SIGMOD-SIGART Sympos. Principles Database Systems (ACM, New York), 159–168.Crossref, Google Scholar
- (2011) A simpler approach to matrix completion. J. Machine Learn. Res. 12(February):3413–3430.Google Scholar
- (2013) A new convex relaxation for tensor completion. Burges CLC, Bottou L, Welling M, Ghahramani Z, Weinberger KQ, eds. Advances in Neural Information Processing Systems, vol. 26 (Curran Associates, Red Hook, NY), 2967–2975.Google Scholar
- (2013) Multilinear multitask learning. Proc. Machine Learn. Res. 28(3): 1444–1452.Google Scholar
- (2014) Collaborative filtering beyond the user-item matrix: A survey of the state of the art and future challenges. ACM Comput. Surveys 47(1):Article 3.Crossref, Google Scholar
- (2014) Learning with tensors: A framework based on convex optimization and spectral regularization. Machine Learn. 94(3):303–351.Crossref, Google Scholar
- (2008) Relational learning via collective matrix factorization. Proc. 14th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 650–658.Crossref, Google Scholar
- (1987) Low-dimensional procedure for the characterization of human faces. J. Optical Soc. Amer. A 4(3):519–524.Crossref, Google Scholar
- (2007) Theory of semidefinite programming for sensor network localization. Math. Programming 109(2–3):367–384.Crossref, Google Scholar
- (2016) Noisy matrix completion under sparse factor models. IEEE Trans. Inform. Theory 62(6):3636–3661.Crossref, Google Scholar
- Statista (2016) Annual number of worldwide active Amazon customer accounts from 1997 to 2015. Accessed December 20, 2016, http://www.statista.com/statistics/237810/number-of-active-amazon-customer-accounts-worldwide/.Google Scholar
- (2005) CubeSVD: A novel approach to personalized web search. Proc. 14th Internat. Conf. World Wide Web (ACM, New York), 382–390.Crossref, Google Scholar
- (2015) Convergence rate of Bayesian tensor estimator and its minimax optimality. Proc. Machine Learn. Res. 37:1273–1282.Google Scholar
- (2013) Convex tensor decomposition via structured Schatten norm regularization. Burges CLC, Bottou L, Welling M, Ghahramani Z, Weinberger KQ, eds. Advances in Neural Information Processing Systems, vol. 26 (Curran Associates, Red Hook, NY), 1331–1339.Google Scholar
- (2011) Statistical performance of convex tensor decomposition. Shawe-Taylor J, Zemel RS Bartlett PL, Pereira F, Weinberger KQ, eds. Advances in Neural Information Processing Systems, vol. 24 (Curran Associates, Red Hook, NY), 972–980.Google Scholar
- (2001) Missing value estimation methods for DNA microarrays. Bioinformatics 17(6):520–525.Crossref, Google Scholar
- (2002) Multilinear analysis of image ensembles: TensorFaces. Heyden A, Sparr G, Nielsen M, Johansen P, eds. Computer Vision—ECCV 2002, Lecture Notes in Computer Science, vol. 2350 (Springer, Berlin), 447–460.Crossref, Google Scholar
- (1978) Cross-validatory estimation of the number of components in factor and principal components models. Technometrics 20(4):397–405.Crossref, Google Scholar
- (2013) Speedup matrix completion with side information: Application to multi-label learning. Burges CLC, Bottou L, Welling M, Ghahramani Z, Weinberger KQ, eds. Advances in Neural Information Processing Systems, vol. 26 (Curran Associates, Red Hook, NY), 2301–2309.Google Scholar
- (1988) On the limit of the largest eigenvalue of the large dimensional sample covariance matrix. Probab. Theory Related Fields 78(4):509–521.Crossref, Google Scholar
- (2015) On tensor completion via nuclear norm minimization. Foundations Comput. Math. 16(4):1031–1068.Crossref, Google Scholar
- (2015) Interpolating convex and non-convex tensor decompositions via the subspace norm. Cortes C, Lawrence ND, Lee DD, Sugiyama M, Garnett R, eds. Advances in Neural Information Processing Systems, vol. 28 (Curran Associates, Red Hook, NY), 3106–3113.Google Scholar
- (2013) Tensor regression with applications in neuroimaging data analysis. J. Amer. Statist. Assoc. 108(502):540–552.Crossref, Google Scholar

