暂无分享,去创建一个
[1] Djallel Bouneffouf,et al. A Survey on Practical Applications of Multi-Armed and Contextual Bandits , 2019, ArXiv.
[2] Kristian Kersting,et al. Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach , 2011, IJCAI.
[3] Kristian Kersting,et al. Gradient-based boosting for statistical relational learning: The relational dependency network case , 2011, Machine Learning.
[4] Joelle Pineau,et al. Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis , 2018, MLHC.
[5] Luc De Raedt,et al. Bayesian Logic Programming: Theory and Tool , 2007 .
[6] Shuo Yang,et al. Identifying Rare Diseases from Behavioural Data: A Machine Learning Approach , 2016, 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).
[7] Kristian Kersting,et al. Generalized First Order Decision Diagrams for First Order Markov Decision Processes , 2009, IJCAI.
[8] Jude W. Shavlik,et al. in Advances in Neural Information Processing , 1996 .
[9] Raymond J. Mooney,et al. Bottom-up learning of Markov logic network structure , 2007, ICML '07.
[10] Lise Getoor,et al. Learning Probabilistic Relational Models , 1999, IJCAI.
[11] Raymond J. Mooney,et al. Online Structure Learning for Markov Logic Networks , 2011, ECML/PKDD.
[12] Ole J. Mengshoel,et al. Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models , 2017, AAAI.
[13] Li Zhou,et al. A Survey on Contextual Multi-armed Bandits , 2015, ArXiv.
[14] Matthew Richardson,et al. Markov logic networks , 2006, Machine Learning.
[15] John Langford,et al. Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits , 2014, ICML.
[16] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[17] John Langford,et al. A Contextual Bandit Bake-off , 2018, J. Mach. Learn. Res..
[18] John Langford,et al. The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information , 2007, NIPS.
[19] Sriraam Natarajan,et al. Identifying Parkinson's Patients: A Functional Gradient Boosting Approach , 2017, AIME.
[20] Shuo Yang,et al. Combining content-based and collaborative filtering for job recommendation system: A cost-sensitive Statistical Relational Learning approach , 2017, Knowl. Based Syst..
[21] Luc De Raedt,et al. ProbLog: A Probabilistic Prolog and its Application in Link Discovery , 2007, IJCAI.
[22] Ben Taskar,et al. Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning) , 2007 .
[23] Devendra Singh Dhami,et al. Non-Parametric Learning of Gaifman Models , 2020, ArXiv.
[24] Sriraam Natarajan,et al. Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities. , 2018, Smart health.
[25] Hendrik Blockeel,et al. Top-Down Induction of First Order Logical Decision Trees , 1998, AI Commun..
[26] Rajeev Rastogi,et al. LogUCB: an explore-exploit algorithm for comments recommendation , 2012, CIKM '12.
[27] Oliver Schulte,et al. The CTU Prague Relational Learning Repository , 2015, ArXiv.
[28] Kristian Kersting,et al. A Machine Learning Pipeline for Three-Way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain , 2012, 2012 11th International Conference on Machine Learning and Applications.
[29] Wei Chu,et al. A contextual-bandit approach to personalized news article recommendation , 2010, WWW '10.