- Q2: memory-based active learning for optimizing noisy continuous functions
Andrew Moore, Jeff Schneider, Justin Boyan, and M.S. Lee
IEEE International Conference on Robotics and Automation (ICRA '00), April, 2000, pp. 4095 - 4102.
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pdf (651KB) | Copyrighted
- Least-Squares Temporal Difference Learning
Justin Boyan
Machine
Learning: Proceedings of the Sixteenth International Conference (ICML '99), 1999.
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pdf (220KB) | Copyrighted
- Stochastic production scheduling to meet demand forecasts
Jeff Schneider, Justin Boyan, and Andrew Moore
Proceedings of the 37th
IEEE Conference on Decision and Control, December, 1998, pp. 2722 - 2727.
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pdf (587KB) | Copyrighted
- Learning Evaluation Functions for Global Optimization
Justin Boyan
doctoral dissertation, tech. report CMU-CS-98-152, Computer Science Department, Carnegie Mellon University, August, 1998
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pdf (2MB) | Copyrighted
- Q2: Memory-based active learning for optimizing noisy continuous functions
Andrew Moore, Jeff Schneider, Justin Boyan, and Mary Lee
International Conference of Machine Learning, June, 1998.
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pdf (721KB) | Copyrighted
- Value Function Based Production Scheduling
Jeff Schneider, Justin Boyan, and Andrew Moore
Machine Learning: Proceedings of the Fifteenth International Conference (ICML '98), March, 1998.
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pdf (144KB) | Copyrighted
- Learning Evaluation Functions for Global Optimization and Boolean Satisfiability
Justin Boyan and Andrew Moore
Fifteenth National Conference on Artificial Intelligence, 1998.
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pdf (240KB) | Copyrighted
- The Anonymizer: Protecting User Privacy on the Web
Justin Boyan
Computer-Mediated Communication
Magazine, Vol. 4, No. 9, September, 1997,
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pdf (19KB) | Copyrighted
- Using Prediction to Improve Combinatorial Optimization Search
Justin Boyan and Andrew Moore
Sixth International Workshop on Artificial Intelligence and Statistics, 1997.
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pdf (201KB) | Copyrighted
- A Machine Learning Architecture for Optimizing Web Search Engines
Justin Boyan, D. Freitag, and T. Joachims
Proceedings of the AAAI workshop on Internet-Based Information Systems, 1996.
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pdf (237KB) | Copyrighted
- Learning Evaluation Functions for Large Acyclic Domains
Justin Boyan and Andrew Moore
Machine Learning: Proceedings of the Thirteenth International Conference, 1996.
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pdf (190KB) | Copyrighted
- Robust Value Function Approximation by Working Backwards
Justin Boyan and Andrew Moore
Proceedings of the Workshop on Value Function Approximation, Machine Learning Conference, July, 1995.
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pdf (213KB) | Copyrighted
- Generalization in Reinforcement Learning: Safely Approximating the Value Function
Justin Boyan and Andrew Moore
Advances in Neural Information Processing Systems 7, 1995.
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pdf (660KB) | Copyrighted
- Packet routing in dynamically changing networks: A reinforcement learning approach
Justin Boyan and Michael Littman
January, 1994.
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pdf (110KB) | Copyrighted
- A Distributed Reinforcement Learning Scheme for Network Routing
M. Littman and Justin Boyan
tech. report CMU-CS-93-165, Robotics Institute, Carnegie Mellon University, 1993
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pdf (105KB) | Copyrighted
- Modular Neural Networks for Learning Context-Dependent Game Strategies
Justin Boyan
doctoral dissertation, Department of Engineering and Computer Laboratory, University of Cambridge, August, 1992
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pdf (454KB) | Copyrighted
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