Graph kernels and Gaussian processes for relational reinforcement learning
暂无分享,去创建一个
[1] N. Aronszajn. Theory of Reproducing Kernels. , 1950 .
[2] Frank Harary,et al. Graph Theory , 2016 .
[3] Stephen Barnett,et al. Matrix Methods for Engineers and Scientists , 1982 .
[4] Gene H. Golub,et al. Matrix computations , 1983 .
[5] C. Watkins. Learning from delayed rewards , 1989 .
[6] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[7] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[8] Alexander Gammerman,et al. Ridge Regression Learning Algorithm in Dual Variables , 1998, ICML.
[9] Richard S. Sutton,et al. Introduction to Reinforcement Learning , 1998 .
[10] Stuart J. Russell,et al. Bayesian Q-Learning , 1998, AAAI/IAAI.
[11] Alexander J. Smola,et al. Learning with kernels , 1998 .
[12] David Haussler,et al. Convolution kernels on discrete structures , 1999 .
[13] Gunnar Rätsch,et al. Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites , 2000, German Conference on Bioinformatics.
[14] W. Imrich,et al. Product Graphs: Structure and Recognition , 2000 .
[15] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[16] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[17] Leslie Pack Kaelbling,et al. Practical Reinforcement Learning in Continuous Spaces , 2000, ICML.
[18] Stefan Schaal,et al. Real-time robot learning with locally weighted statistical learning , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).
[19] Nello Cristianini,et al. Classification using String Kernels , 2000 .
[20] Kurt Driessens,et al. Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner , 2001, ECML.
[21] Bernhard Schölkopf,et al. Some kernels for structured data , 2001 .
[22] George Karypis,et al. Frequent subgraph discovery , 2001, Proceedings 2001 IEEE International Conference on Data Mining.
[23] Luc De Raedt,et al. Machine Learning: ECML 2001 , 2001, Lecture Notes in Computer Science.
[24] Xin Wang,et al. Batch Value Function Approximation via Support Vectors , 2001, NIPS.
[25] Michael Collins,et al. Convolution Kernels for Natural Language , 2001, NIPS.
[26] Hisashi Kashima,et al. Kernels for graph classification , 2002 .
[27] Thore Graepel,et al. PAC-Bayesian Pattern Classification with kernels , 2002 .
[28] Saso Dzeroski,et al. Integrating Experimentation and Guidance in Relational Reinforcement Learning , 2002, ICML.
[29] George Karypis,et al. Automated Approaches for Classifying Structures , 2002, BIOKDD.
[30] Jeffrey M. Forbes,et al. Representations for learning control policies , 2002 .
[31] Thomas Gärtner,et al. Kernels for structured data , 2008, Series in Machine Perception and Artificial Intelligence.
[32] Tomaso Poggio,et al. Everything old is new again: a fresh look at historical approaches in machine learning , 2002 .
[33] Mehryar Mohri,et al. Positive Definite Rational Kernels , 2003, COLT.
[34] Hisashi Kashima,et al. Marginalized Kernels Between Labeled Graphs , 2003, ICML.
[35] Thomas Gärtner,et al. Graph kernels and Gaussian processes for relational reinforcement learning , 2006, Machine-mediated learning.
[36] Carl E. Rasmussen,et al. Gaussian Processes in Reinforcement Learning , 2003, NIPS.
[37] Thomas Gärtner,et al. A survey of kernels for structured data , 2003, SKDD.
[38] Shie Mannor,et al. Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning , 2003, ICML.
[39] Thomas Gärtner,et al. On Graph Kernels: Hardness Results and Efficient Alternatives , 2003, COLT.
[40] Kurt Driessens,et al. Relational Instance Based Regression for Relational Reinforcement Learning , 2003, ICML.
[41] Peter A Flach,et al. Proceedings of the 16th Annual Conference on Computational Learning Theory and 7th Kernel Workshop , 2003 .
[42] Saso Dzeroski,et al. Multi-relational data mining: an introduction , 2003, SKDD.
[43] Thomas Gärtner,et al. Cyclic pattern kernels for predictive graph mining , 2004, KDD.
[44] Saso Dzeroski,et al. Integrating Guidance into Relational Reinforcement Learning , 2004, Machine Learning.
[45] Erik D. Demaine,et al. Tetris is hard, even to approximate , 2002, Int. J. Comput. Geom. Appl..
[46] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[47] Liming Xiang,et al. Kernel-Based Reinforcement Learning , 2006, ICIC.
[48] Jens Vygen,et al. The Book Review Column1 , 2020, SIGACT News.
[49] Iain Murray,et al. Introduction To Gaussian Processes , 2008 .
[50] De,et al. Relational Reinforcement Learning , 2022 .