Moore, Andrew W.

76 publications

IJCAI 2011 Theoretical Justification of Popular Link Prediction Heuristics Purnamrita Sarkar, Deepayan Chakrabarti, Andrew W. Moore

COLT 2010 Theoretical Justification of Popular Link Prediction Heuristics Purnamrita Sarkar, Deepayan Chakrabarti, Andrew W. Moore

ICML 2008 Fast Incremental Proximity Search in Large Graphs Purnamrita Sarkar, Andrew W. Moore, Amit Prakash

JMLR 2008 Forecasting Web Page Views: Methods and Observations Jia Li, Andrew W. Moore

UAI 2007 A Tractable Approach to Finding Closest Truncated-Commute-Time Neighbors in Large Graphs Purnamrita Sarkar, Andrew W. Moore

AISTATS 2007 Fast State Discovery for HMM Model Selection and Learning Sajid M. Siddiqi, Geogrey J. Gordon, Andrew W. Moore

ICML 2006 Machine Learning, Proceedings of the Twenty-Third International Conference (ICML 2006), Pittsburgh, Pennsylvania, USA, June 25-29, 2006 William W. Cohen, Andrew W. Moore

AAAI 2006 Monitoring Food Safety by Detecting Patterns in Consumer Complaints Artur Dubrawski, Kimberly Elenberg, Andrew W. Moore, Maheshkumar Sabhnani

JMLR 2006 New Algorithms for Efficient High-Dimensional Nonparametric Classification Ting Liu, Andrew W. Moore, Alexander Gray

ICML 2006 Sequential Update of ADtrees Josep Roure, Andrew W. Moore

NeurIPS 2005 A Bayesian Spatial Scan Statistic Daniel B. Neill, Andrew W. Moore, Gregory F. Cooper

NeurIPS 2005 Dual-Tree Fast Gauss Transforms Dongryeol Lee, Andrew W. Moore, Alexander G. Gray

NeurIPS 2005 Dynamic Social Network Analysis Using Latent Space Models Purnamrita Sarkar, Andrew W. Moore

ICML 2005 Fast Inference and Learning in Large-State-Space HMMs Sajid M. Siddiqi, Andrew W. Moore

NeurIPS 2005 Fast Information Value for Graphical Models Brigham S. Anderson, Andrew W. Moore

NeurIPS 2005 Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery Jeremy Kubica, Joseph Masiero, Robert Jedicke, Andrew Connolly, Andrew W. Moore

NeurIPS 2004 Active Learning for Anomaly and Rare-Category Detection Dan Pelleg, Andrew W. Moore

NeurIPS 2004 An Investigation of Practical Approximate Nearest Neighbor Algorithms Ting Liu, Andrew W. Moore, Ke Yang, Alexander G. Gray

NeurIPS 2004 Detecting Significant Multidimensional Spatial Clusters Daniel B. Neill, Andrew W. Moore, Francisco Pereira, Tom M. Mitchell

ICML 2004 Tractable Learning of Large Bayes Net Structures from Sparse Data Anna Goldenberg, Andrew W. Moore

NeurIPS 2003 A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters Daniel B. Neill, Andrew W. Moore

ICML 2003 Bayesian Network Anomaly Pattern Detection for Disease Outbreaks Weng-Keen Wong, Andrew W. Moore, Gregory F. Cooper, Michael M. Wagner

AISTATS 2003 Fast Robust Logistic Regression for Large Sparse Datasets with Binary Outputs Paul Komarek, Andrew W. Moore

ICML 2003 Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G. Schneider

NeurIPS 2003 New Algorithms for Efficient High Dimensional Non-Parametric Classification Ting Liu, Andrew W. Moore, Alexander Gray

ICML 2003 Optimal Reinsertion: A New Search Operator for Accelerated and More Accurate Bayesian Network Structure Learning Andrew W. Moore, Weng-Keen Wong

AISTATS 2003 Rapid Evaluation of Multiple Density Models Alexander G. Gray, Andrew W. Moore

UAI 2002 Interpolating Conditional Density Trees Scott Davies, Andrew W. Moore

JMLR 2002 Policy Search Using Paired Comparisons Malcolm J. A. Strens, Andrew W. Moore

UAI 2002 Real-Valued All-Dimensions Search: Low-Overhead Rapid Searching over Subsets of Attributes Andrew W. Moore, Jeff G. Schneider

AAAI 2002 Rule-Based Anomaly Pattern Detection for Detecting Disease Outbreaks Weng-Keen Wong, Andrew W. Moore, Gregory F. Cooper, Michael M. Wagner

AAAI 2002 Stochastic Link and Group Detection Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider, Yiming Yang

NeurIPS 2002 Using Tarjan's Red Rule for Fast Dependency Tree Construction Dan Pelleg, Andrew W. Moore

MLJ 2002 Variable Resolution Discretization in Optimal Control Rémi Munos, Andrew W. Moore

ICML 2001 Direct Policy Search Using Paired Statistical Tests Malcolm J. A. Strens, Andrew W. Moore

ICML 2001 Mixtures of Rectangles: Interpretable Soft Clustering Dan Pelleg, Andrew W. Moore

ICML 2001 Repairing Faulty Mixture Models Using Density Estimation Peter Sand, Andrew W. Moore

ICML 2000 A Dynamic Adaptation of AD-Trees for Efficient Machine Learning on Large Data Sets Paul Komarek, Andrew W. Moore

ICML 2000 A Nonparametric Approach to Noisy and Costly Optimization Brigham S. Anderson, Andrew W. Moore, David Cohn

JMLR 2000 Learning Evaluation Functions to Improve Optimization by Local Search Justin Boyan, Andrew W. Moore

ICML 2000 Learning Filaments Geoffrey J. Gordon, Andrew W. Moore

UAI 2000 Mix-Nets: Factored Mixtures of Gaussians in Bayesian Networks with Mixed Continuous and Discrete Variables Scott Davies, Andrew W. Moore

ICML 2000 Rates of Convergence for Variable Resolution Schemes in Optimal Control Rémi Munos, Andrew W. Moore

UAI 2000 The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data Andrew W. Moore

ICML 2000 X-Means: Extending K-Means with Efficient Estimation of the Number of Clusters Dan Pelleg, Andrew W. Moore

NeurIPS 2000 `n-Body' Problems in Statistical Learning Alexander G. Gray, Andrew W. Moore

ICML 1999 Distributed Value Functions Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore, Martin A. Riedmiller

IJCAI 1999 Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs Andrew W. Moore, Leemon C. Baird Iii, Leslie Pack Kaelbling

IJCAI 1999 Variable Resolution Discretization for High-Accuracy Solutions of Optimal Control Problems Rémi Munos, Andrew W. Moore

AAAI 1998 Applying Online Search Techniques to Continuous-State Reinforcement Learning Scott Davies, Andrew Y. Ng, Andrew W. Moore

NeurIPS 1998 Barycentric Interpolators for Continuous Space and Time Reinforcement Learning Rémi Munos, Andrew W. Moore

JAIR 1998 Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets Andrew W. Moore, Mary S. Lee

NeurIPS 1998 Gradient Descent for General Reinforcement Learning Leemon C. Baird Iii, Andrew W. Moore

AAAI 1998 Learning Evaluation Functions for Global Optimization and Boolean Satisfiability Justin A. Boyan, Andrew W. Moore

ICML 1998 Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions Andrew W. Moore, Jeff G. Schneider, Justin A. Boyan, Mary S. Lee

ICML 1998 Value Function Based Production Scheduling Jeff G. Schneider, Justin A. Boyan, Andrew W. Moore

NeurIPS 1998 Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees Andrew W. Moore

ICML 1997 Efficient Locally Weighted Polynomial Regression Predictions Andrew W. Moore, Jeff G. Schneider, Kan Deng

AISTATS 1997 Using Prediction to Improve Combinatorial Optimization Search Justin A. Boyan, Andrew W. Moore

ICML 1996 Learning Evaluation Functions for Large Acyclic Domains Justin A. Boyan, Andrew W. Moore

ICML 1996 Reinforcement Learning in Factories: The Auton Project (Abstract) Andrew W. Moore

JAIR 1996 Reinforcement Learning: A Survey Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore

NeurIPS 1995 Memory-Based Stochastic Optimization Andrew W. Moore, Jeff G. Schneider

IJCAI 1995 Multiresolution Instance-Based Learning Kan Deng, Andrew W. Moore

MLJ 1995 The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces Andrew W. Moore, Christopher G. Atkeson

ICML 1994 Efficient Algorithms for Minimizing Cross Validation Error Andrew W. Moore, Mary S. Lee

NeurIPS 1994 Generalization in Reinforcement Learning: Safely Approximating the Value Function Justin A. Boyan, Andrew W. Moore

NeurIPS 1993 Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation Oded Maron, Andrew W. Moore

NeurIPS 1993 Memory-Based Methods for Regression and Classification Thomas G. Dietterich, Dietrich Wettschereck, Chris G. Atkeson, Andrew W. Moore

MLJ 1993 Prioritized Sweeping: Reinforcement Learning with Less Data and Less Time Andrew W. Moore, Christopher G. Atkeson

NeurIPS 1993 The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces Andrew W. Moore

NeurIPS 1992 Memory-Based Reinforcement Learning: Efficient Computation with Prioritized Sweeping Andrew W. Moore, Christopher G. Atkeson

NeurIPS 1991 Fast, Robust Adaptive Control by Learning Only Forward Models Andrew W. Moore

ICML 1991 Variable Resolution Dynamic Programming Andrew W. Moore

NeurIPS 1990 A VLSI Neural Network for Color Constancy Andrew W. Moore, John Allman, Geoffrey Fox, Rodney Goodman

ICML 1990 Acquisition of Dynamic Control Knowledge for a Robotic Manipulator Andrew W. Moore