暂无分享,去创建一个
Zheng Wen | Csaba Szepesvári | Branislav Kveton | Sumeet Katariya | Csaba Szepesvari | B. Kveton | Zheng Wen | S. Katariya
[1] Wtt Wtt. Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits , 2015 .
[2] Bhaskar Krishnamachari,et al. Combinatorial Network Optimization With Unknown Variables: Multi-Armed Bandits With Linear Rewards and Individual Observations , 2010, IEEE/ACM Transactions on Networking.
[3] Wei Chen,et al. Combinatorial Partial Monitoring Game with Linear Feedback and Its Applications , 2014, ICML.
[4] David Maxwell Chickering,et al. Modeling Contextual Factors of Click Rates , 2007, AAAI.
[5] Nicolò Cesa-Bianchi,et al. Gambling in a rigged casino: The adversarial multi-armed bandit problem , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.
[6] Wei Chen,et al. Combinatorial multi-armed bandit: general framework, results and applications , 2013, ICML 2013.
[7] M. de Rijke,et al. Click Models for Web Search , 2015, Click Models for Web Search.
[8] S. Katariya. Bandits : Learning to Rank with Multiple Clicks , 2018 .
[9] Branislav Kveton,et al. Efficient Learning in Large-Scale Combinatorial Semi-Bandits , 2014, ICML.
[10] Csaba Szepesvári,et al. Partial Monitoring with Side Information , 2012, ALT.
[11] Filip Radlinski,et al. Learning diverse rankings with multi-armed bandits , 2008, ICML '08.
[12] T. L. Lai Andherbertrobbins. Asymptotically Efficient Adaptive Allocation Rules , 1985 .
[13] Zheng Wen,et al. Influence Maximization with Semi-Bandit Feedback , 2016, ArXiv.
[14] Zheng Wen,et al. Cascading Bandits: Learning to Rank in the Cascade Model , 2015, ICML.
[15] Susan T. Dumais,et al. Improving Web Search Ranking by Incorporating User Behavior Information , 2019, SIGIR Forum.
[16] Zheng Wen,et al. Combinatorial Cascading Bandits , 2015, NIPS.
[17] Matthew Richardson,et al. Predicting clicks: estimating the click-through rate for new ads , 2007, WWW '07.
[18] Nick Craswell,et al. An experimental comparison of click position-bias models , 2008, WSDM '08.
[19] Chao Liu,et al. Efficient multiple-click models in web search , 2009, WSDM '09.
[20] Aurélien Garivier,et al. The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond , 2011, COLT.
[21] Olivier Chapelle,et al. A dynamic bayesian network click model for web search ranking , 2009, WWW '09.
[22] Zheng Wen,et al. Cascading Bandits for Large-Scale Recommendation Problems , 2016, UAI.
[23] Alexandre Proutière,et al. Combinatorial Bandits Revisited , 2015, NIPS.
[24] Filip Radlinski,et al. Query chains: learning to rank from implicit feedback , 2005, KDD '05.
[25] Chao Liu,et al. Click chain model in web search , 2009, WWW '09.
[26] Filip Radlinski,et al. Ranked bandits in metric spaces: learning diverse rankings over large document collections , 2013, J. Mach. Learn. Res..
[27] Alexandre Proutière,et al. Learning to Rank , 2015, SIGMETRICS.
[28] Csaba Szepesvári,et al. An adaptive algorithm for finite stochastic partial monitoring , 2012, ICML.
[29] Zheng Wen,et al. Matroid Bandits: Fast Combinatorial Optimization with Learning , 2014, UAI.
[30] D. Teneketzis,et al. Asymptotically Efficient Adaptive Allocation Schemes for Controlled I.I.D. Processes: Finite Paramet , 1988 .
[31] Csaba Szepesvári,et al. Partial Monitoring - Classification, Regret Bounds, and Algorithms , 2014, Math. Oper. Res..
[32] Zheng Wen,et al. Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits , 2014, AISTATS.