Explore-exploit in top-N recommender systems via Gaussian processes
暂无分享,去创建一个
Andreas Krause | Fabio De Bona | Hastagiri P. Vanchinathan | Isidor Nikolic | Andreas Krause | F. D. Bona | I. Nikolic
[1] Filip Radlinski,et al. Learning optimally diverse rankings over large document collections , 2010, ICML.
[2] W. Bruce Croft,et al. Linear feature-based models for information retrieval , 2007, Information Retrieval.
[3] Risi Kondor,et al. Diffusion kernels on graphs and other discrete structures , 2002, ICML 2002.
[4] Bracha Shapira,et al. Recommender Systems Handbook , 2010, Springer US.
[5] Eli Upfal,et al. Multi-Armed Bandits in Metric Spaces ∗ , 2008 .
[6] Susan T. Dumais,et al. Improving Web Search Ranking by Incorporating User Behavior Information , 2019, SIGIR Forum.
[7] John D. Lafferty,et al. Diffusion Kernels on Graphs and Other Discrete Input Spaces , 2002, ICML.
[8] Anthony Widjaja,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.
[9] Andreas Krause,et al. Online Learning of Assignments , 2009, NIPS.
[10] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[11] Christopher K. I. Williams,et al. Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) , 2005 .
[12] Roberto Turrin,et al. Performance of recommender algorithms on top-n recommendation tasks , 2010, RecSys '10.
[13] Andreas Krause,et al. Contextual Gaussian Process Bandit Optimization , 2011, NIPS.
[14] Wei Chu,et al. Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms , 2010, WSDM '11.
[15] Nick Craswell,et al. An experimental comparison of click position-bias models , 2008, WSDM '08.
[16] Ronny Lempel. Recommendation challenges in web media settings , 2012, RecSys '12.
[17] Wei Chu,et al. A contextual-bandit approach to personalized news article recommendation , 2010, WWW '10.
[18] Yoram Singer,et al. An Efficient Boosting Algorithm for Combining Preferences by , 2013 .
[19] Andreas Krause,et al. Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization , 2012, ICML.
[20] Yisong Yue,et al. Linear Submodular Bandits and their Application to Diversified Retrieval , 2011, NIPS.
[21] Wei Chu,et al. A case study of behavior-driven conjoint analysis on Yahoo!: front page today module , 2009, KDD.
[22] Andreas Krause,et al. Budgeted Nonparametric Learning from Data Streams , 2010, ICML.
[23] Wei Chu,et al. Contextual Bandits with Linear Payoff Functions , 2011, AISTATS.
[24] Robert E. Schapire,et al. Non-Stochastic Bandit Slate Problems , 2010, NIPS.