A Theoretical Analysis of Query Selection for Collaborative Filtering

Keywords

Combinatorics, Function (biology), Integer (computer science), Mathematics, Polynomial

References

• Malicious Omissions and Errors in Answers to Membership QueriesDana Angluin, Mārtiņš Kriķis, Robert H. Sloan — 1997
• Collaborative Filtering Using Weighted Majority Prediction AlgorithmsAtsuyoshi Nakamura, Naoki Abe — 1998
• An open architecture for collaborative filtering of netnewsPaul Resnick — 1994
• Constructing Optimal Binary Decision Trees is NP-CompleteLaurent Hyafil, Ronald L. Rivest — 1976
• How many queries are needed to learn?Lisa Hellerstein, Vijay Raghavan, Krishnan Pillaipakkamnatt — 1995
• Oracles and queries that are sufficient for exact learning (extended abstract)Nader H. Bshouty, Richard Cleve, Sampath Kannan — 1994
• A threshold of ln n for approximating set cover (preliminary version)Uriel Feige — 1996
• Decision trees for geometric modelsEsther M. Arkin, Henk Meijer, Joseph S. B. Mitchell — 1993
• Approximation algorithms for combinatorial problemsDavid S. Johnson — 1973
• Efficient search for approximate nearest neighbor in high dimensional spacesEyal Kushilevitz, Rafail Ostrovsky, Yuval Rabani — 1998
• Query by committeeH. Sebastian Seung, Manfred Opper, Haim Sompolinsky — 1992
• Generalized Teaching Dimensions and the Query Complexity of LearningTibor Hegedüs — 1995
• Quantum versus classical learnabilityRocco A. Servedio, Steven J. Gortler — 2000
• Queries and concept learningDana Angluin — 1988
• An optimal algorithm for approximate nearest neighbor searching fixed dimensionsSunil Arya, David M. Mount, Nathan S. Netanyahu — 1998
• Queries revisitedDana Angluin — 2001
• Empirical Analysis of Predictive Algorithms for Collaborative FilteringJohn S. Breese, David Heckerman, Carl Kadie — 1998
• GroupLensPaul Resnick, Neophytos Iacovou, Mitesh Suchak — 1994
• Approximate nearest neighborsPiotr Indyk, Rajeev Motwani — 1998
• Approximate Nearest Neighbors: Towards Removing the Curse of DimensionalityPiotr Indyk, Rajeev Motwani — 1998

Cited by

• Output Divergence Criterion for Active Learning in Collaborative SettingsNeil Rubens, Ryota Tomioka, Sugiayama Masashi — 2008
• Semantic feedback for hybrid recommendations in RecommendzMatthew Garden, Gregory Dudek — 2005
• Interactive Submodular Set CoverAndrew Guillory, Jeff Bilmes — 2010
• The SeniorGezond Recommender: exploration put into practiceVera Hollink, M.W. van Someren, Stephan ten Hagen — 2007
• Optimizing hierarchical menus : a usage-based approachVera Hollink — 2008
• Recommending Informative LinksVera Hollink, M.W. van Someren, Simen Hagen — 2005
• Learning with matrix factorizationsNathan Srebro, Tommi Jaakkola — 2004
• A general dimension for query learningJosé L. Balcázar, Jorge Castro, David Guijarro — 2007
• Analysis of a greedy active learning strategySanjoy Dasgupta — 2004
• Generalization Error Bounds for Collaborative Prediction with Low-Rank MatricesNathan Srebro, Noga Alon, Tommi Jaakkola — 2004
• WI/IAT 2003 Workshop on Applications, Products and Services of Web-based Support SystemsJingTao Yao, Pawan Lingras — 2003
• Simultaneous Learning and Covering with Adversarial NoiseAndrew Guillory, Jeff Bilmes — 2011
• Collaborative active learningChan Chang-Tik, Gillian Kidman, Meng Yew Tee — 2009
• Minimal Interaction Search: Multi-Way Search with Item CategoriesSandilya Bhamidipati, Branislav Kveton, S. Muthukrishnan — 2013
• Active Learning and Submodular FunctionsJeffrey A. Bilmes, Andrew Guillory — 2012
• Learning with non-Standard SupervisionRuth Urner — 2013
• ON THE USE OF SEMANTIC FEEDBACK IN RECOMMENDER SYSTEMSMatthew Garden — 2004
• Sequential Bayesian SearchWen Zheng, Branislav Kveton, Brian Eriksson — 2013
• On User Recommendations Based on Multiple CuesG. Dudek, M. Garden — 2003
• Recommendation And Visualization Techniques For large Scale Data. (Les Techniques De Recommandation Et De Visualisation Pour Les Données A Une Grande Echelle)Afshin Moin — 2012

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