Memory-Based Reinforcement Learning: Efficient Computation with Prioritized Sweeping. - Andrew W. Moore 001; Christopher G. Atkeson (NIPS, 1992)

Memory-Based Methods for Regression and Classification. - Thomas G. Dietterich; Dietrich Wettschereck; Christopher G. Atkeson; Andrew W. Moore 001 (NIPS, 1993)

Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation. - Oded Maron; Andrew W. Moore 001 (NIPS, 1993)

The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces. - Andrew W. Moore 001 (NIPS, 1993)

Prioritized Sweeping: Reinforcement Learning With Less Data and Less Time. - Andrew W. Moore 001; Christopher G. Atkeson (Mach. Learn., 1993)

Efficient Algorithms for Minimizing Cross Validation Error. - Andrew W. Moore 001; Mary S. Lee (ICML, 1994)

Generalization in Reinforcement Learning: Safely Approximating the Value Function. - Justin A. Boyan; Andrew W. Moore 001 (NIPS, 1994)

Multiresolution Instance-Based Learning. - Kan Deng; Andrew W. Moore 001 (IJCAI, 1995)

Memory-based Stochastic Optimization. - Andrew W. Moore 001; Jeff G. Schneider (NIPS, 1995)

The Parti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces. - Andrew W. Moore 001; Christopher G. Atkeson (Mach. Learn., 1995)

Learning Evaluation Functions for Large Acyclic Domains. - Justin A. Boyan; Andrew W. Moore 001 (ICML, 1996)

Reinforcement Learning in Factories: The Auton Project (Abstract). - Andrew W. Moore 001 (ICML, 1996)

Reinforcement Learning: A Survey. - Leslie Pack Kaelbling; Michael L. Littman; Andrew W. Moore 001 (J. Artif. Intell. Res., 1996)

Using Prediction to Improve Combinatorial Optimization Search. - Justin A. Boyan; Andrew W. Moore 001 (AISTATS, 1997)

Learning to recognize time series: combining ARMA models with memory-based learning. - Kan Deng; Andrew W. Moore 001; Michael C. Nechyba (CIRA, 1997)

Efficient Locally Weighted Polynomial Regression Predictions. - Andrew W. Moore 001; Jeff G. Schneider; Kan Deng (ICML, 1997)

Locally Weighted Learning. - Christopher G. Atkeson; Andrew W. Moore 001; Stefan Schaal (Artif. Intell. Rev., 1997)

Locally Weighted Learning for Control. - Christopher G. Atkeson; Andrew W. Moore 001; Stefan Schaal (Artif. Intell. Rev., 1997)

The Racing Algorithm: Model Selection for Lazy Learners. - Oded Maron; Andrew W. Moore 001 (Artif. Intell. Rev., 1997)

Learning Evaluation Functions for Global Optimization and Boolean Satisfiability. - Justin A. Boyan; Andrew W. Moore 001 (AAAI/IAAI, 1998)

Applying Online Search Techniques to Continuous-State Reinforcement Learning. - Scott Davies; Andrew Y. Ng; Andrew W. Moore 001 (AAAI/IAAI, 1998)

Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions. - Andrew W. Moore 001; 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 001 (ICML, 1998)

ADtrees for Fast Counting and for Fast Learning of Association Rules. - Brigham S. Anderson; Andrew W. Moore 001 (KDD, 1998)

Gradient Descent for General Reinforcement Learning. - Leemon C. Baird III; Andrew W. Moore 001 (NIPS, 1998)

Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees. - Andrew W. Moore 001 (NIPS, 1998)

Barycentric Interpolators for Continuous Space and Time Reinforcement Learning. - Rémi Munos; Andrew W. Moore 001 (NIPS, 1998)

Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets. - Andrew W. Moore 001; Mary S. Lee (J. Artif. Intell. Res., 1998)

Distributed Value Functions. - Jeff G. Schneider; Weng-Keen Wong; Andrew W. Moore 001; Martin A. Riedmiller (ICML, 1999)

Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs. - Andrew W. Moore 001; 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 001 (IJCAI, 1999)

Gradient descent approaches to neural-net-based solutions of the Hamilton-Jacobi-Bellman equation. - Rémi Munos; Leemon C. Baird III; Andrew W. Moore 001 (IJCNN, 1999)

Bayesian Networks for Lossless Dataset Compression. - Scott Davies; Andrew W. Moore 001 (KDD, 1999)

Accelerating Exact k-means Algorithms with Geometric Reasoning. - Dan Pelleg; Andrew W. Moore 001 (KDD, 1999)

Reinforcement Learning for Cooperating and Communicating Reactive Agents in Electrical Power Grids. - Martin A. Riedmiller; Andrew W. Moore 001; Jeff G. Schneider (Balancing Reactivity and Social Deliberation in Multi-Agent Systems, 2000)

A Nonparametric Approach to Noisy and Costly Optimization. - Brigham S. Anderson; Andrew W. Moore 001; David Cohn (ICML, 2000)

Learning Filaments. - Geoffrey J. Gordon; Andrew W. Moore 001 (ICML, 2000)

A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets. - Paul Komarek; Andrew W. Moore 001 (ICML, 2000)

Rates of Convergence for Variable Resolution Schemes in Optimal Control. - Rémi Munos; Andrew W. Moore 001 (ICML, 2000)

X-means: Extending K-means with Efficient Estimation of the Number of Clusters. - Dan Pelleg; Andrew W. Moore 001 (ICML, 2000)

'N-Body' Problems in Statistical Learning. - Alexander G. Gray; Andrew W. Moore 001 (NIPS, 2000)

Mix-nets: Factored Mixtures of Gaussians in Bayesian Networks with Mixed Continuous And Discrete Variables. - Scott Davies; Andrew W. Moore 001 (UAI, 2000)

The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data. - Andrew W. Moore 001 (UAI, 2000)

Learning Evaluation Functions to Improve Optimization by Local Search. - Justin A. Boyan; Andrew W. Moore 001 (J. Mach. Learn. Res., 2000)

Mixtures of Rectangles: Interpretable Soft Clustering. - Dan Pelleg; Andrew W. Moore 001 (ICML, 2001)

Repairing Faulty Mixture Models using Density Estimation. - Peter Sand; Andrew W. Moore 001 (ICML, 2001)

Direct Policy Search using Paired Statistical Tests. - Malcolm J. A. Strens; Andrew W. Moore 001 (ICML, 2001)

Classification-Driven Pathological Neuroimage Retrieval Using Statistical Asymmetry Measures. - Yanxi Liu 001; Frank Dellaert; William E. Rothfus; Andrew W. Moore 001; Jeff G. Schneider; Takeo Kanade (MICCAI, 2001)

Stochastic Link and Group Detection. - Jeremy Kubica; Andrew W. Moore 001; Jeff G. Schneider; Yiming Yang (AAAI/IAAI, 2002)

Rule-Based Anomaly Pattern Detection for Detecting Disease Outbreaks. - Weng-Keen Wong; Andrew W. Moore 001; Gregory F. Cooper; Michael M. Wagner 001 (AAAI/IAAI, 2002)

Data, network, and application: technical description of the Utah RODS Winter Olympic Biosurveillance System. - Fu-Chiang Tsui; Jeremy U. Espino; Michael M. Wagner 001; Per H. Gesteland; Oleg Ivanov; Robert T. Olszewski; Zhen Liu; Xiaoming Zeng; Wendy W. Chapman; Weng-Keen Wong; Andrew W. Moore 001 (AMIA, 2002)

Using Tarjan's Red Rule for Fast Dependency Tree Construction. - Dan Pelleg; Andrew W. Moore 001 (NIPS, 2002)

Interpolating Conditional Density Trees. - Scott Davies; Andrew W. Moore 001 (UAI, 2002)

Real-valued All-Dimensions Search: Low-overhead Rapid Searching over Subsets of Attributes. - Andrew W. Moore 001; Jeff G. Schneider (UAI, 2002)

Policy Search using Paired Comparisons. - Malcolm J. A. Strens; Andrew W. Moore 001 (J. Mach. Learn. Res., 2002)

Variable Resolution Discretization in Optimal Control. - Rémi Munos; Andrew W. Moore 001 (Mach. Learn., 2002)

Rapid Evaluation of Multiple Density Models. - Alexander G. Gray; Andrew W. Moore 001 (AISTATS, 2003)

Fast Robust Logistic Regression for Large Sparse Datasets with Binary Outputs. - Paul Komarek; Andrew W. Moore 001 (AISTATS, 2003)

Probabilistic Noise Identification and Data Cleaning. - Jeremy Kubica; Andrew W. Moore 001 (ICDM, 2003)

Tractable Group Detection on Large Link Data Sets. - Jeremy Kubica; Andrew W. Moore 001; Jeff G. Schneider (ICDM, 2003)

Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries. - Jeremy Kubica; Andrew W. Moore 001; David Cohn; Jeff G. Schneider (ICML, 2003)

Optimal Reinsertion: A New Search Operator for Accelerated and More Accurate Bayesian Network Structure Learning. - Andrew W. Moore 001; Weng-Keen Wong (ICML, 2003)

Bayesian Network Anomaly Pattern Detection for Disease Outbreaks. - Weng-Keen Wong; Andrew W. Moore 001; Gregory F. Cooper; Michael M. Wagner 001 (ICML, 2003)

New Algorithms for Efficient High Dimensional Non-parametric Classification. - Ting Liu 006; Andrew W. Moore 001; Alexander G. Gray (NIPS, 2003)

A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters. - Daniel B. Neill; Andrew W. Moore 001 (NIPS, 2003)

Nonparametric Density Estimation: Toward Computational Tractability. - Alexander G. Gray; Andrew W. Moore 001 (SDM, 2003)

Application of Information Technology: Automated Syndromic Surveillance for the 2002 Winter Olympics. - Per H. Gesteland; Reed M. Gardner; Fu-Chiang Tsui; Jeremy U. Espino; Robert T. Rolfs; Brent C. James; Wendy Webber Chapman; Andrew W. Moore 001; Michael M. Wagner 001 (J. Am. Medical Informatics Assoc., 2003)

Tractable learning of large Bayes net structures from sparse data. - Anna Goldenberg; Andrew W. Moore 001 (ICML, 2004)

Fast nonlinear regression via eigenimages applied to galactic morphology. - Brigham S. Anderson; Andrew W. Moore 001; Andrew J. Connolly; Robert Nichol (KDD, 2004)

Belief state approaches to signaling alarms in surveillance systems. - Kaustav Das; Andrew W. Moore 001; Jeff G. Schneider (KDD, 2004)

The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data. - Ting Liu 006; Ke Yang 005; Andrew W. Moore 001 (KDD, 2004)

Rapid detection of significant spatial clusters. - Daniel B. Neill; Andrew W. Moore 001 (KDD, 2004)

An Investigation of Practical Approximate Nearest Neighbor Algorithms. - Ting Liu 006; Andrew W. Moore 001; Alexander G. Gray; Ke Yang 005 (NIPS, 2004)

Detecting Significant Multidimensional Spatial Clusters. - Daniel B. Neill; Andrew W. Moore 001; Francisco Pereira 001; Tom M. Mitchell (NIPS, 2004)

Active Learning for Anomaly and Rare-Category Detection. - Dan Pelleg; Andrew W. Moore 001 (NIPS, 2004)

Making Logistic Regression a Core Data Mining Tool with TR-IRLS. - Paul Komarek; Andrew W. Moore 001 (ICDM, 2005)

Fast inference and learning in large-state-space HMMs. - Sajid M. Siddiqi; Andrew W. Moore 001 (ICML, 2005)

Bayes net graphs to understand co-authorship networks? - Anna Goldenberg; Andrew W. Moore 001 (LinkKDD, 2005)

A multiple tree algorithm for the efficient association of asteroid observations. - Jeremy Kubica; Andrew W. Moore 001; Andrew J. Connolly; Robert Jedicke (KDD, 2005)

Detection of emerging space-time clusters. - Daniel B. Neill; Andrew W. Moore 001; Maheshkumar Sabhnani; Kenny Daniel (KDD, 2005)

Fast Information Value for Graphical Models. - Brigham S. Anderson; Andrew W. Moore 001 (NIPS, 2005)

Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery. - Jeremy Kubica; Joseph Masiero; Andrew W. Moore 001; Robert Jedicke; Andrew J. Connolly (NIPS, 2005)

Dual-Tree Fast Gauss Transforms. - Dongryeol Lee; Alexander G. Gray; Andrew W. Moore 001 (NIPS, 2005)

A Bayesian Spatial Scan Statistic. - Daniel B. Neill; Andrew W. Moore 001; Gregory F. Cooper (NIPS, 2005)

Algorithms for rapid outbreak detection: a research synthesis. - David L. Buckeridge; Howard S. Burkom; Murray Campbell; William R. Hogan; Andrew W. Moore 001 (J. Biomed. Informatics, 2005)

What's Strange About Recent Events (WSARE): An Algorithm for the Early Detection of Disease Outbreaks. - Weng-Keen Wong; Andrew W. Moore 001; Gregory F. Cooper; Michael M. Wagner 001 (J. Mach. Learn. Res., 2005)

Dynamic social network analysis using latent space models. - Purnamrita Sarkar; Andrew W. Moore 001 (SIGKDD Explor., 2005)

Monitoring Food Safety by Detecting Patterns in Consumer Complaints. - Artur Dubrawski; Kimberly Elenberg; Andrew W. Moore 001; Maheshkumar Sabhnani (AAAI, 2006)

Sequential update of ADtrees. - Josep Roure; Andrew W. Moore 001 (ICML, 2006)

New cached-sufficient statistics algorithms for quickly answering statistical questions. - Andrew W. Moore 001 (KDD, 2006)

Autonomous Visualization. - Khalid El-Arini; Andrew W. Moore 001; Ting Liu 006 (PKDD, 2006)

New Algorithms for Efficient High-Dimensional Nonparametric Classification. - Ting Liu 006; Andrew W. Moore 001; Alexander G. Gray (J. Mach. Learn. Res., 2006)

Dependency trees in sub-linear time and bounded memory. - Dan Pelleg; Andrew W. Moore 001 (VLDB J., 2006)

A Tractable Approach to Finding Closest Truncated-commute-time Neighbors in Large Graphs. - Purnamrita Sarkar; Andrew W. Moore 001 (UAI, 2007)

Fast State Discovery for HMM Model Selection and Learning. - Sajid M. Siddiqi; Geoffrey J. Gordon; Andrew W. Moore 001 (AISTATS, 2007)

Fast incremental proximity search in large graphs. - Purnamrita Sarkar; Andrew W. Moore 001; Amit Prakash (ICML, 2008)

Fast dynamic reranking in large graphs. - Purnamrita Sarkar; Andrew W. Moore 001 (WWW, 2009)

Fast nearest-neighbor search in disk-resident graphs. - Purnamrita Sarkar; Andrew W. Moore 001 (KDD, 2010)

Computationally efficient scoring of activity using demographics and connectivity of entities. - Artur Dubrawski; John Östlund; Lujie Chen; Andrew W. Moore 001 (Inf. Technol. Manag., 2010)

Random Walks in Social Networks and their Applications: A Survey. - Purnamrita Sarkar; Andrew W. Moore 001 (Social Network Data Analytics, 2011)

Theoretical Justification of Popular Link Prediction Heuristics. - Purnamrita Sarkar; Deepayan Chakrabarti; Andrew W. Moore 001 (IJCAI, 2011)

The Anchors Hierachy: Using the triangle inequality to survive high dimensional data - Andrew W. Moore 001 (CoRR, 2013)

Four Thought Leaders on Where the Industry Is Headed. - Andrew W. Moore 001; Tim O'Reilly; Paul D. Nielsen; Kevin Fall (IEEE Softw., 2016)