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Auton Project
This project is no longer active.
Head: Jeff Schneider and Andrew Moore
Contact: Jeff Schneider
Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
Associated lab(s) / group(s):
 Auton Lab
Project Homepage
Publications
  • Making Logistic Regression A Core Data Mining Tool: A Practical Investigation of Accuracy, Speed, and Simplicity

    Paul Komarek and Andrew Moore
    tech. report CMU-RI-TR-05-27, Robotics Institute, Carnegie Mellon University, May, 2005
    Details | pdf (215KB) | Copyrighted

  • Efficient Algorithms for the Identification of Potential Track/Observation Associations in Continuous Time Data

    Jeremy Martin Kubica, Andrew Moore, Andrew J. Connolly, and Robert Jedicke
    tech. report CMU-RI-TR-05-10, Robotics Institute, Carnegie Mellon University, March, 2005
    Details | pdf (168KB) | Copyrighted

  • Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery

    Jeremy Martin Kubica, Joseph Masiero, Andrew Moore, Robert Jedicke, and Andrew J. Connolly
    Neural Information Processing Systems, December, 2005.
    Details | pdf (205KB) | Copyrighted

  • Scalable and robust group discovery on large transactional data

    Pak Yan Choi, Andrew Moore, and Jeremy Martin Kubica
    tech. report CMU-RI-TR-05-60, Robotics Institute, Carnegie Mellon University, December, 2005
    Details | pdf (753KB) | Copyrighted

  • Efficient Discovery of Spatial Associations and Structure with Application to Asteroid Tracking

    Jeremy Martin Kubica
    doctoral dissertation, tech. report CMU-RI-TR-06-01, Robotics Institute, Carnegie Mellon University, December, 2005
    Details | pdf (7MB) | Copyrighted

  • Fast Nonlinear Regression via Eigenimages Applied to Galactic Morphology

    Brigham Anderson, Andrew Moore, Andrew J. Connolly, and Robert Nichol
    International Conference on Knowledge Discovery and Data Mining, August, 2004.
    Details

  • Logistic Regression for Data Mining and High-Dimensional Classification

    Paul Komarek
    tech. report CMU-RI-TR-04-34, Robotics Institute, Carnegie Mellon University, May, 2004
    Details | pdf (2MB) | Copyrighted

  • Alias Detection in Link Data Sets

    Paul Hsiung
    master's thesis, tech. report CMU-RI-TR-04-22, Robotics Institute, Carnegie Mellon University, March, 2004
    Details | pdf (89KB) | Copyrighted

  • Spatial Data Structures for Efficient Trajectory-Based Queries

    Jeremy Martin Kubica, Andrew Moore, Andrew J. Connolly, and Robert Jedicke
    tech. report CMU-RI-TR-04-61, Robotics Institute, Carnegie Mellon University, November, 2004
    Details | pdf (511KB) | Copyrighted

  • Fast and Robust Track Initiation Using Multiple Trees

    Jeremy Martin Kubica, Andrew Moore, Andrew J. Connolly, and Robert Jedicke
    tech. report CMU-RI-TR-04-62, Robotics Institute, Carnegie Mellon University, November, 2004
    Details | pdf (1MB) | Copyrighted

  • Covariant Policy Search

    J. Andrew (Drew) Bagnell and Jeff Schneider
    Proceeding of the International Joint Conference on Artifical Intelligence, August, 2003.
    Details | pdf (136KB) | Copyrighted

  • Policy Search by Dynamic Programming

    J. Andrew (Drew) Bagnell, Sham Kakade, Andrew Ng, and Jeff Schneider
    Neural Information Processing Systems, December, 2003.
    Details | pdf (157KB) | Copyrighted

  • Learning with scope; with application to information extraction and classification

    David Blei, J. Andrew (Drew) Bagnell, and Andrew McCallum
    Uncertainty in Artificial Intelligence, June, 2002, pp. 53-60.
    Details | pdf (132KB) | Copyrighted

  • Solving Uncertain Markov Decision Problems

    J. Andrew (Drew) Bagnell, Andrew Y. Ng, and Jeff Schneider
    tech. report CMU-RI-TR-01-25, Robotics Institute, Carnegie Mellon University, August, 2001
    Details | pdf (970KB) | Copyrighted

  • Autonomous Helicopter Control using Reinforcement Learning Policy Search Methods

    J. Andrew (Drew) Bagnell and Jeff Schneider
    Proceedings of the International Conference on Robotics and Automation 2001, May, 2001.
    Details | pdf (224KB) | Copyrighted

  • Mix-nets: Factored Mixtures of Gaussians in Bayesian Networks with Mixed Continuous and Discrete Variables

    Scott Davies and Andrew Moore
    tech. report CMU-CS-00-119, Computer Science Department, Carnegie Mellon University, April, 2000
    Details | pdf (406KB) | Copyrighted

  • Variable resolution discretization for high-accuracy solutions of optimal control problems

    Remi Munos and Andrew Moore
    International Joint Conference on Artificial Intelligence, August, 1999.
    Details | pdf (431KB) | Copyrighted

  • Gradient Descent Approaches to Neural-Net-Based Solutions of the Hamilton-Jacobi-Bellman Equation

    Remi Munos, Leemon Baird, and Andrew Moore
    International Joint Conference on Neural Networks, July, 1999.
    Details | pdf (192KB) | Copyrighted

  • Cached Sufficient Statistics for Automated Mining and Discovery from Massive Data Sources

    Andrew Moore, Jeff Schneider, Brigham Anderson, Scott Davies, Paul Komarek, Mary Soon Lee, Marina Meila, Remi Munos, Kary Myers, and Dan Pelleg
    July, 1999.
    Details | pdf (192KB) | Copyrighted

  • Reinforcement Learning Through Gradient Descent

    Leemon Baird
    doctoral dissertation, tech. report CMU-CS-99-132, Computer Science Department, Carnegie Mellon University, May, 1999
    Details | pdf (244KB) | Copyrighted

  • Influence and Variance of a Markov Chain: Application to Adaptive Discretization in Optimal Control

    Remi Munos and Andrew Moore
    IEEE Conference on Decision and Control, December, 1999, pp. 1464 - 1469.
    Details | pdf (207KB) | Copyrighted

  • Variable Resolution Discretization in Optimal Control

    Remi Munos and Andrew Moore
    Machine Learning Journal, , 1999
    Details | pdf (535KB) | Copyrighted

  • Regret bounds for prediction problems

    Geoffrey Gordon
    Proceedings of COLT '99, 1999.
    Details | pdf (207KB) | Copyrighted

  • Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs

    Andrew Moore, Leemon Baird, and Leslie Pack Kaelbling
    Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI '99), 1999.
    Details | pdf (414KB) | Copyrighted

  • Gradient Descent for General Reinforcement Learning

    Leemon Baird and Andrew Moore
    Advances in Neural Information Processing Systems 11, , 1999
    Details | pdf (48KB) | Copyrighted

  • Distributed Value Functions

    Jeff Schneider, Weng-Keen Wong, Andrew Moore, and Martin Riedmiller
    International Conference on Machine Learning, 1999.
    Details | pdf (150KB) | Copyrighted

  • Bayesian Networks for Lossless Dataset Compression

    Scott Davies and Andrew Moore
    1999 Knowledge Discovery from Databases (KDD '99), 1999.
    Details | pdf (144KB) | Copyrighted

  • Approximate Solutions to Markov Decision Processes

    Geoffrey Gordon
    doctoral dissertation, tech. report , Computer Science Department, Carnegie Mellon University, 1999
    Details | pdf (1MB) | Copyrighted

  • Accelerating Exact k-means Algorithms with Geometric Reasoning

    Dan Pelleg and Andrew Moore
    Knowledge Discovery from Databases (KDD '99), 1999.
    Details | pdf (438KB) | Copyrighted

  • A Study of Reinforcement Learning in the Continuous Case by the Means of Viscosity Solutions

    Remi Munos
    Machine Learning Journal, , 1999
    Details | pdf (360KB) | Copyrighted

  • ADtrees for Fast Counting and for Fast Learning of Association Rules

    Brigham Anderson and Andrew Moore
    Knowledge Discovery from Databases '98, , August, 1998,
    Details | pdf (55KB) | 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.
    Details | 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.
    Details | pdf (144KB) | Copyrighted

  • Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets

    Andrew Moore and Mary Soon Lee
    Journal of Artificial Intelligence Research, Vol. 8, March, 1998, pp. 67- 91.
    Details | pdf (260KB) | Copyrighted

  • Very Fast EM-based Mixture Model Clustering using Multiresolution kd-trees

    Andrew Moore
    Neural Information Systems Processing, , December, 1998,
    Details | pdf (306KB) | Copyrighted

  • Barycentric Interpolator for Continuous Space and Time Reinforcement Learning

    Remi Munos and Andrew Moore
    Neural Information Processing Systems, December, 1998.
    Details | pdf (170KB) | Copyrighted

  • Learning Evaluation Functions for Global Optimization and Boolean Satisfiability

    Justin Boyan and Andrew Moore
    Fifteenth National Conference on Artificial Intelligence, 1998.
    Details | pdf (240KB) | Copyrighted

  • Applying Online Search Techniques to Reinforcement Learning

    Scott Davies, A. Y. Ng, and Andrew Moore
    Fifteenth National Conference on Artificial Intelligence (AAAI), 1998.
    Details | pdf (234KB) | Copyrighted

  • A general convergence method for Reinforcement Learning in the continuous case

    Remi Munos
    European Conference on Machine Learning, 1998.
    Details | pdf (579KB) | Copyrighted

  • Reinforcement Learning for Continuous Stochastic Control Problems

    Remi Munos and Paul Bourgine
    Neural Information Processing Systems, 1997.
    Details | pdf (454KB) | Copyrighted

  • Locally Weighted Learning For Control

    Andrew Moore, C. G. Atkeson, and S. A. Schaal
    AI Review, Vol. 11, 1997, pp. 75-113.
    Details | pdf (788KB) | Copyrighted

  • Locally Weighted Learning

    C. G. Atkeson, S. A. Schaal, and Andrew Moore
    AI Review, Vol. 11, 1997, pp. 11-73.
    Details | pdf (972KB) | Copyrighted

  • Finite-Element methods with local triangulation refinement for continuous Reinforcement Learning problems

    Remi Munos
    European Conference on Machine Learning 1997, 1997.
    Details | pdf (569KB) | Copyrighted

  • Efficient Locally Weighted Polynomial Regression Predictions

    Andrew Moore, Jeff Schneider, and Kan Deng
    International Conference on Machine Learning, 1997.
    Details | pdf (246KB) | Copyrighted

  • A convergent Reinforcement Learning algorithm in the continuous case based on a Finite Difference method

    Remi Munos
    1997 International Joint Conference on Artificial Intelligence (IJCAI '97), 1997.
    Details | pdf (658KB) | Copyrighted

  • Using Finite-Differences methods for approximating the value function of continuous Reinforcement Learning problems

    Remi Munos
    International Symposium on Multi-Technology Information Processing 1996, 1996.
    Details | pdf (315KB) | Copyrighted

  • Reinforcement Learning: A Survey

    L.P. Kaelbling, M.L. Littman, and Andrew Moore
    Journal of Artificial Intelligence Research, Vol. 4, 1996, pp. 237-285.
    Details | pdf (442KB) | Copyrighted

  • Learning Evaluation Functions for Large Acyclic Domains

    Justin Boyan and Andrew Moore
    Machine Learning: Proceedings of the Thirteenth International Conference, 1996.
    Details | pdf (190KB) | Copyrighted

  • Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning

    Jeff Schneider
    Neural Information Processing Systems 9, 1996.
    Details | pdf (160KB) | Copyrighted

  • A Convergent Reinforcement Learning algorithm in the continuous case: the Finite-Element Reinforcement Learning

    Remi Munos
    International Conference on Machine Learning 1996 (ICML '96), 1996.
    Details | pdf (202KB) | Copyrighted

  • Memory-Based Learning for Control

    Andrew Moore, C. G. Atkeson, and S. A. Schaal
    tech. report CMU-RI-TR-95-18, Robotics Institute, Carnegie Mellon University, April, 1995
    Details | pdf (731KB) | Copyrighted

  • Learning Automated Product Recommendations Without Observable Features: An Initial Investigation

    Mary S. Lee and Andrew Moore
    tech. report CMU-RI-TR-95-17, Robotics Institute, Carnegie Mellon University, April, 1995
    Details | pdf (237KB) | Copyrighted

  • The Parti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces

    Andrew Moore and C. G. Atkeson
    Machine Learning, Vol. 21, December, 1995,
    Details | pdf (758KB) | Copyrighted

  • Stable Function Approximation in Dynamic Programming

    Geoffrey Gordon
    Proceedings of IMCL '95, 1995.
    Details | pdf (169KB) | Copyrighted

  • Online Fitted Reinforcement Learning

    Geoffrey Gordon
    VFA workshop at ML-95, 1995.
    Details | pdf (88KB) | Copyrighted

  • Multiresolution Instance-Based Learning

    Andrew Moore, Jeff Schneider, and Kan Deng
    Proceedings of International Joint Conference on Artificial Intelligence, 1995.
    Details | pdf (78KB) | Copyrighted

  • Memory-based Stochastic Optimization

    Andrew Moore and Jeff Schneider
    Neural Information Processing Systems 8, 1995.
    Details | pdf (269KB) | Copyrighted

  • Generalization in Reinforcement Learning: Safely Approximating the Value Function

    Justin Boyan and Andrew Moore
    Advances in Neural Information Processing Systems 7, 1995.
    Details | pdf (660KB) | Copyrighted

  • Efficient Algorithms for Minimizing Cross Validation Error

    Andrew Moore and M. S. Lee
    Proceedings of the 11th International Conference on Machine Learning, 1994.
    Details | pdf (116KB) | Copyrighted

  • An Empirical Investigation of Brute Force to choose Features, Smoothers and Function Approximators

    Andrew Moore, D. J. Hill, and M. P . Johnson
    Computational Learning Theory and Natural Learning Systems, Vol. 3, 1994,
    Details | pdf (412KB) | Copyrighted

  • Prioritized Sweeping: Reinforcement Learning with Less Data and Less Real Time

    Andrew Moore and C. G. Atkeson
    Machine Learning, Vol. 13, October, 1993,
    Details | pdf (571KB) | Copyrighted

  • Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation

    O. Maron and Andrew Moore
    Advances in Neural Information ProcessingSystems 6, 1993.
    Details | pdf (141KB) | Copyrighted

  • Memory-based Reinforcement Learning: Efficient Computation with Prioritized Sweeping

    Andrew Moore and C. G. Atkeson
    Advances in Neural Information Processing Systems 5, 1992.
    Details

  • Knowledge of Knowledge and Intelligent Experimentation for Learning Control

    Andrew Moore
    Proceedings of the 1991 Seattle International Joint Conference on Neural Networks, July, 1991, pp. 683 - 688.
    Details | pdf (426KB) | Copyrighted

  • Variable Resolution Dynamic Programming: Efficiently Learning Action Maps in Multivariate Real-valued State-spaces

    Andrew Moore
    Proceedings of the Eighth International Conference on Machine Learning, 1991.
    Details

  • Fast, Robust Adaptive Control by Learning only Forward Models

    Andrew Moore
    1991.
    Details

  • Acquisition of Dynamic Control Knowledge for a Robotic Manipulator

    Andrew Moore
    Proceedings of the 7th International Conference on Machine Learning, 1990.
    Details

  • Some Experiments in Adaptive State Space Robotics

    W. F. Clocksin and Andrew Moore
    Proceedings of the 7th AISB Conference, 1989.
    Details