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Auton Project
This project is no longer active.
Head: Andrew Moore and Jeff Schneider
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, February, 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, pp. 67- 91, March, 1998.
    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, pp. 75-113, 1997.
    Details | pdf (788KB) | Copyrighted

  • Locally Weighted Learning

    C. G. Atkeson, S. A. Schaal, and Andrew Moore
    AI Review, Vol. 11, pp. 11-73, 1997.
    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, pp. 237-285, 1996.
    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