Andrew W. Moore

Publication Activity (10 Years)

Years Active: 1992-2016
Publications (10 Years): 1

Top Venues

IEEE Softw.

Publications

Andrew W. Moore, Tim O'Reilly, Paul D. Nielsen, Kevin Fall
Four Thought Leaders on Where the Industry Is Headed. IEEE Softw. 33 (1) (2016)
Andrew W. Moore, Jeff G. Schneider
Real-valued All-Dimensions search: Low-overhead rapid searching over subsets of attributes CoRR (2013)
Scott Davies, Andrew W. Moore
Mix-nets: Factored Mixtures of Gaussians in Bayesian Networks With Mixed Continuous And Discrete Variables CoRR (2013)
Andrew W. Moore
The Anchors Hierachy: Using the triangle inequality to survive high dimensional data CoRR (2013)
Scott Davies, Andrew W. Moore
Interpolating Conditional Density Trees CoRR (2013)
Purnamrita Sarkar, Andrew W. Moore
A Tractable Approach to Finding Closest Truncated-commute-time Neighbors in Large Graphs CoRR (2012)
Dongryeol Lee, Alexander G. Gray, Andrew W. Moore
Dual-Tree Fast Gauss Transforms CoRR (2011)
Purnamrita Sarkar, Deepayan Chakrabarti, Andrew W. Moore
Theoretical Justification of Popular Link Prediction Heuristics. IJCAI (2011)
Purnamrita Sarkar, Deepayan Chakrabarti, Andrew W. Moore
Theoretical Justification of Popular Link Prediction Heuristics. COLT (2010)
Artur Dubrawski, John Östlund, Lujie Chen, Andrew W. Moore
Computationally efficient scoring of activity using demographics and connectivity of entities. Inf. Technol. Manag. 11 (2) (2010)
Purnamrita Sarkar, Andrew W. Moore
Fast nearest-neighbor search in disk-resident graphs. KDD (2010)
Purnamrita Sarkar, Andrew W. Moore
Fast dynamic reranking in large graphs. WWW (2009)
Purnamrita Sarkar, Andrew W. Moore, Amit Prakash
Fast incremental proximity search in large graphs. ICML (2008)
Purnamrita Sarkar, Andrew W. Moore
A Tractable Approach to Finding Closest Truncated-commute-time Neighbors in Large Graphs. UAI (2007)
Sajid M. Siddiqi, Geoffrey J. Gordon, Andrew W. Moore
Fast State Discovery for HMM Model Selection and Learning. AISTATS (2007)
Josep Roure, Andrew W. Moore
Sequential update of ADtrees. ICML (2006)
Khalid El-Arini, Andrew W. Moore, Ting Liu
Autonomous Visualization. PKDD (2006)
Artur Dubrawski, Kimberly Elenberg, Andrew W. Moore, Maheshkumar Sabhnani
Monitoring Food Safety by Detecting Patterns in Consumer Complaints. AAAI (2006)
Dan Pelleg, Andrew W. Moore
Dependency trees in sub-linear time and bounded memory. VLDB J. 15 (3) (2006)
Ting Liu, Andrew W. Moore, Alexander G. Gray
New Algorithms for Efficient High-Dimensional Nonparametric Classification. J. Mach. Learn. Res. 7 (2006)
Andrew W. Moore
New cached-sufficient statistics algorithms for quickly answering statistical questions. KDD (2006)
Brigham Anderson, Andrew W. Moore
Fast Information Value for Graphical Models. NIPS (2005)
Dongryeol Lee, Alexander G. Gray, Andrew W. Moore
Dual-Tree Fast Gauss Transforms. NIPS (2005)
Paul Komarek, Andrew W. Moore
Making Logistic Regression a Core Data Mining Tool with TR-IRLS. ICDM (2005)
Sajid M. Siddiqi, Andrew W. Moore
Fast inference and learning in large-state-space HMMs. ICML (2005)
David L. Buckeridge, Howard S. Burkom, Murray Campbell, William R. Hogan, Andrew W. Moore
Algorithms for rapid outbreak detection: a research synthesis. J. Biomed. Informatics 38 (2) (2005)
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabhnani, Kenny Daniel
Detection of emerging space-time clusters. KDD (2005)
Purnamrita Sarkar, Andrew W. Moore
Dynamic social network analysis using latent space models. SIGKDD Explor. 7 (2) (2005)
Jeremy Kubica, Andrew W. Moore, Andrew J. Connolly, Robert Jedicke
A multiple tree algorithm for the efficient association of asteroid observations. KDD (2005)
Jeremy Kubica, Joseph Masiero, Andrew W. Moore, Robert Jedicke, Andrew J. Connolly
Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery. NIPS (2005)
Purnamrita Sarkar, Andrew W. Moore
Dynamic Social Network Analysis using Latent Space Models. NIPS (2005)
Weng-Keen Wong, Andrew W. Moore, Gregory F. Cooper, Michael M. Wagner
What's Strange About Recent Events (WSARE): An Algorithm for the Early Detection of Disease Outbreaks. J. Mach. Learn. Res. 6 (2005)
Daniel B. Neill, Andrew W. Moore, Gregory F. Cooper
A Bayesian Spatial Scan Statistic. NIPS (2005)
Brigham Anderson, Andrew W. Moore, Andrew J. Connolly, Robert Nichol
Fast nonlinear regression via eigenimages applied to galactic morphology. KDD (2004)
Daniel B. Neill, Andrew W. Moore
Rapid detection of significant spatial clusters. KDD (2004)
Ting Liu, Ke Yang, Andrew W. Moore
The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data. KDD (2004)
Kaustav Das, Andrew W. Moore, Jeff G. Schneider
Belief state approaches to signaling alarms in surveillance systems. KDD (2004)
Daniel B. Neill, Andrew W. Moore, Francisco Pereira, Tom M. Mitchell
Detecting Significant Multidimensional Spatial Clusters. NIPS (2004)
Ting Liu, Andrew W. Moore, Alexander G. Gray, Ke Yang
An Investigation of Practical Approximate Nearest Neighbor Algorithms. NIPS (2004)
Dan Pelleg, Andrew W. Moore
Active Learning for Anomaly and Rare-Category Detection. NIPS (2004)
Paul Komarek, Andrew W. Moore
Fast Robust Logistic Regression for Large Sparse Datasets with Binary Outputs. AISTATS (2003)
Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider
Tractable Group Detection on Large Link Data Sets. ICDM (2003)
Per H. Gesteland, Reed M. Gardner, Fu-Chiang Tsui, Jeremy U. Espino, Robert T. Rolfs, Brent C. James, Wendy Webber Chapman, Andrew W. Moore, Michael M. Wagner
Application of Information Technology: Automated Syndromic Surveillance for the 2002 Winter Olympics. J. Am. Medical Informatics Assoc. 10 (6) (2003)
Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G. Schneider
Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries. ICML (2003)
Ting Liu, Andrew W. Moore, Alexander G. Gray
New Algorithms for Efficient High Dimensional Non-parametric Classification. NIPS (2003)
Andrew W. Moore, Weng-Keen Wong
Optimal Reinsertion: A New Search Operator for Accelerated and More Accurate Bayesian Network Structure Learning. ICML (2003)
Alexander G. Gray, Andrew W. Moore
Nonparametric Density Estimation: Toward Computational Tractability. SDM (2003)
Daniel B. Neill, Andrew W. Moore
A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters. NIPS (2003)
Weng-Keen Wong, Andrew W. Moore, Gregory F. Cooper, Michael M. Wagner
Bayesian Network Anomaly Pattern Detection for Disease Outbreaks. ICML (2003)
Alexander G. Gray, Andrew W. Moore
Rapid Evaluation of Multiple Density Models. AISTATS (2003)
Jeremy Kubica, Andrew W. Moore
Probabilistic Noise Identification and Data Cleaning. ICDM (2003)
Dan Pelleg, Andrew W. Moore
Using Tarjan's Red Rule for Fast Dependency Tree Construction. NIPS (2002)
Fu-Chiang Tsui, Jeremy U. Espino, Michael M. Wagner, Per H. Gesteland, Oleg Ivanov, Robert T. Olszewski, Zhen Liu, Xiaoming Zeng, Wendy W. Chapman, Weng-Keen Wong, Andrew W. Moore
Data, network, and application: technical description of the Utah RODS Winter Olympic Biosurveillance System. AMIA (2002)
Andrew W. Moore, Jeff G. Schneider
Real-valued All-Dimensions Search: Low-overhead Rapid Searching over Subsets of Attributes. UAI (2002)
Weng-Keen Wong, Andrew W. Moore, Gregory F. Cooper, Michael M. Wagner
Rule-Based Anomaly Pattern Detection for Detecting Disease Outbreaks. AAAI/IAAI (2002)
Rémi Munos, Andrew W. Moore
Variable Resolution Discretization in Optimal Control. Mach. Learn. 49 (2-3) (2002)
Scott Davies, Andrew W. Moore
Interpolating Conditional Density Trees. UAI (2002)
Malcolm J. A. Strens, Andrew W. Moore
Policy Search using Paired Comparisons. J. Mach. Learn. Res. 3 (2002)
Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider, Yiming Yang
Stochastic Link and Group Detection. AAAI/IAAI (2002)
Dan Pelleg, Andrew W. Moore
Mixtures of Rectangles: Interpretable Soft Clustering. ICML (2001)
Malcolm J. A. Strens, Andrew W. Moore
Direct Policy Search using Paired Statistical Tests. ICML (2001)
Peter Sand, Andrew W. Moore
Repairing Faulty Mixture Models using Density Estimation. ICML (2001)
Yanxi Liu, Frank Dellaert, William E. Rothfus, Andrew W. Moore, Jeff G. Schneider, Takeo Kanade
Classification-Driven Pathological Neuroimage Retrieval Using Statistical Asymmetry Measures. MICCAI (2001)
Scott Davies, Andrew W. Moore
Mix-nets: Factored Mixtures of Gaussians in Bayesian Networks with Mixed Continuous And Discrete Variables. UAI (2000)
Andrew W. Moore
The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data. UAI (2000)
Alexander G. Gray, Andrew W. Moore
'N-Body' Problems in Statistical Learning. NIPS (2000)
Rémi Munos, Andrew W. Moore
Rates of Convergence for Variable Resolution Schemes in Optimal Control. ICML (2000)
Dan Pelleg, Andrew W. Moore
X-means: Extending K-means with Efficient Estimation of the Number of Clusters. ICML (2000)
Geoffrey J. Gordon, Andrew W. Moore
Learning Filaments. ICML (2000)
Andrew W. Moore, Jeff G. Schneider, Justin A. Boyan, Mary S. Lee
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions. ICRA (2000)
Justin A. Boyan, Andrew W. Moore
Learning Evaluation Functions to Improve Optimization by Local Search. J. Mach. Learn. Res. 1 (2000)
Martin A. Riedmiller, Andrew W. Moore, Jeff G. Schneider
Reinforcement Learning for Cooperating and Communicating Reactive Agents in Electrical Power Grids. Balancing Reactivity and Social Deliberation in Multi-Agent Systems (2000)
Brigham S. Anderson, Andrew W. Moore, David Cohn
A Nonparametric Approach to Noisy and Costly Optimization. ICML (2000)
Paul Komarek, Andrew W. Moore
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets. ICML (2000)
Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore, Martin A. Riedmiller
Distributed Value Functions. ICML (1999)
Rémi Munos, Andrew W. Moore
Variable Resolution Discretization for High-Accuracy Solutions of Optimal Control Problems. IJCAI (1999)
Dan Pelleg, Andrew W. Moore
-means Algorithms with Geometric Reasoning. KDD (1999)
Andrew W. Moore, Leemon C. Baird III, Leslie Pack Kaelbling
Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs. IJCAI (1999)
Scott Davies, Andrew W. Moore
Bayesian Networks for Lossless Dataset Compression. KDD (1999)
Rémi Munos, Leemon C. Baird III, Andrew W. Moore
Gradient descent approaches to neural-net-based solutions of the Hamilton-Jacobi-Bellman equation. IJCNN (1999)
Brigham S. Anderson, Andrew W. Moore
ADtrees for Fast Counting and for Fast Learning of Association Rules. KDD (1998)
Rémi Munos, Andrew W. Moore
Barycentric Interpolators for Continuous Space and Time Reinforcement Learning. NIPS (1998)
Andrew W. Moore, Mary S. Lee
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets CoRR (1998)
Justin A. Boyan, Andrew W. Moore
Learning Evaluation Functions for Global Optimization and Boolean Satisfiability. AAAI/IAAI (1998)
Scott Davies, Andrew Y. Ng, Andrew W. Moore
Applying Online Search Techniques to Continuous-State Reinforcement Learning. AAAI/IAAI (1998)
Andrew W. Moore, Mary S. Lee
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets. J. Artif. Intell. Res. 8 (1998)
Jeff G. Schneider, Justin A. Boyan, Andrew W. Moore
Value Function Based Production Scheduling. ICML (1998)
Andrew W. Moore, Jeff G. Schneider, Justin A. Boyan, Mary S. Lee
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions. ICML (1998)
Andrew W. Moore
Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees. NIPS (1998)
Leemon C. Baird III, Andrew W. Moore
Gradient Descent for General Reinforcement Learning. NIPS (1998)
Justin A. Boyan, Andrew W. Moore
Using Prediction to Improve Combinatorial Optimization Search. AISTATS (1997)
Christopher G. Atkeson, Andrew W. Moore, Stefan Schaal
Locally Weighted Learning. Artif. Intell. Rev. 11 (1-5) (1997)
Andrew W. Moore, Jeff G. Schneider, Kan Deng
Efficient Locally Weighted Polynomial Regression Predictions. ICML (1997)
Christopher G. Atkeson, Andrew W. Moore, Stefan Schaal
Locally Weighted Learning for Control. Artif. Intell. Rev. 11 (1-5) (1997)
Kan Deng, Andrew W. Moore, Michael C. Nechyba
Learning to recognize time series: combining ARMA models with memory-based learning. CIRA (1997)
Oded Maron, Andrew W. Moore
The Racing Algorithm: Model Selection for Lazy Learners. Artif. Intell. Rev. 11 (1-5) (1997)
Justin A. Boyan, Andrew W. Moore
Learning Evaluation Functions for Large Acyclic Domains. ICML (1996)
Andrew W. Moore
Reinforcement Learning in Factories: The Auton Project (Abstract). ICML (1996)
Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore
Reinforcement Learning: A Survey CoRR (1996)
Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore
Reinforcement Learning: A Survey. J. Artif. Intell. Res. 4 (1996)

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Publication Activity (10 Years)

Top Topics

Top Venues

Andrew W. Moore