| * | 2009 |
|---|
| 108 | EE | Marco Canini,
Wei Li,
Andrew W. Moore,
Raffaele Bolla:
GTVS: Boosting the Collection of Application Traffic Ground Truth.
TMA 2009: 54-63 |
| 107 | EE | Purnamrita Sarkar,
Andrew W. Moore:
Fast dynamic reranking in large graphs.
WWW 2009: 31-40 |
| 106 | EE | Wei Li,
Marco Canini,
Andrew W. Moore,
Raffaele Bolla:
Efficient application identification and the temporal and spatial stability of classification schema.
Computer Networks 53(6): 790-809 (2009) |
| 2008 |
|---|
| 105 | EE | Purnamrita Sarkar,
Andrew W. Moore,
Amit Prakash:
Fast incremental proximity search in large graphs.
ICML 2008: 896-903 |
| 104 | EE | Hamed Haddadi,
Damien Fay,
Steve Uhlig,
Andrew W. Moore,
Richard Mortier,
Almerima Jamakovic,
Miguel Rio:
Tuning Topology Generators Using Spectral Distributions.
SIPEW 2008: 154-173 |
| 103 | EE | Hamed Haddadi,
Damien Fay,
Almerima Jamakovic,
Olaf Maennel,
Andrew W. Moore,
Richard Mortier,
Miguel Rio,
Steve Uhlig:
Beyond Node Degree: Evaluating AS Topology Models
CoRR abs/0807.2023: (2008) |
| 102 | EE | Hamed Haddadi,
Steve Uhlig,
Andrew W. Moore,
Richard Mortier,
Miguel Rio:
Modeling internet topology dynamics.
Computer Communication Review 38(2): 65-68 (2008) |
| 101 | EE | Tim Strayer,
Mark Allman,
Grenville J. Armitage,
Steve Bellovin,
Shudong Jin,
Andrew W. Moore:
IMRG workshop on application classification and identification report.
Computer Communication Review 38(3): 87-90 (2008) |
| 100 | EE | Hamed Haddadi,
Miguel Rio,
Gianluca Iannaccone,
Andrew W. Moore,
Richard Mortier:
Network topologies: Inference, modeling, and generation.
IEEE Communications Surveys and Tutorials 10(1-4): 48-69 (2008) |
| 2007 |
|---|
| 99 | EE | Wei Li,
Andrew W. Moore:
A Machine Learning Approach for Efficient Traffic Classification.
MASCOTS 2007: 310-317 |
| 98 | EE | Tom Auld,
Andrew W. Moore,
Stephen F. Gull:
Bayesian Neural Networks for Internet Traffic Classification.
IEEE Transactions on Neural Networks 18(1): 223-239 (2007) |
| 2006 |
|---|
| 97 | | Artur Dubrawski,
Kimberly Elenberg,
Andrew W. Moore,
Maheshkumar Sabhnani:
Monitoring Food Safety by Detecting Patterns in Consumer Complaints.
AAAI 2006 |
| 96 | EE | Wei Li,
Andrew W. Moore:
Learning for accurate classification of real-time traffic.
CoNEXT 2006: 36 |
| 95 | EE | Awais Ahmed Awan,
Andrew W. Moore:
Synergy: blending heterogeneous measurement elements for effective network monitoring.
CoNEXT 2006: 41 |
| 94 | EE | Josep Roure,
Andrew W. Moore:
Sequential update of ADtrees.
ICML 2006: 769-776 |
| 93 | EE | Khalid El-Arini,
Andrew W. Moore,
Ting Liu:
Autonomous Visualization.
PKDD 2006: 495-502 |
| 92 | EE | Ting Liu,
Andrew W. Moore,
Alexander G. Gray:
New Algorithms for Efficient High-Dimensional Nonparametric Classification.
Journal of Machine Learning Research 7: 1135-1158 (2006) |
| 91 | EE | Dan Pelleg,
Andrew W. Moore:
Dependency trees in sub-linear time and bounded memory.
VLDB J. 15(3): 250-262 (2006) |
| 2005 |
|---|
| 90 | EE | Paul Komarek,
Andrew W. Moore:
Making Logistic Regression a Core Data Mining Tool with TR-IRLS.
ICDM 2005: 685-688 |
| 89 | EE | Sajid M. Siddiqi,
Andrew W. Moore:
Fast inference and learning in large-state-space HMMs.
ICML 2005: 800-807 |
| 88 | EE | Jeremy Kubica,
Andrew W. Moore,
Andrew Connolly,
Robert Jedicke:
A multiple tree algorithm for the efficient association of asteroid observations.
KDD 2005: 138-146 |
| 87 | EE | Daniel B. Neill,
Andrew W. Moore,
Maheshkumar Sabhnani,
Kenny Daniel:
Detection of emerging space-time clusters.
KDD 2005: 218-227 |
| 86 | EE | Daniel B. Neill,
Andrew W. Moore,
Gregory F. Cooper:
A Bayesian Spatial Scan Statistic.
NIPS 2005 |
| 85 | EE | Dongryeol Lee,
Alexander G. Gray,
Andrew W. Moore:
Dual-Tree Fast Gauss Transforms.
NIPS 2005 |
| 84 | EE | Purnamrita Sarkar,
Andrew W. Moore:
Dynamic Social Network Analysis using Latent Space Models.
NIPS 2005 |
| 83 | EE | Brigham Anderson,
Andrew W. Moore:
Fast Information Value for Graphical Models.
NIPS 2005 |
| 82 | EE | Jeremy Kubica,
Joseph Masiero,
Andrew W. Moore,
Robert Jedicke,
Andrew Connolly:
Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery.
NIPS 2005 |
| 81 | EE | Denis Zuev,
Andrew W. Moore:
Traffic Classification Using a Statistical Approach.
PAM 2005: 321-324 |
| 80 | EE | Andrew W. Moore,
Konstantina Papagiannaki:
Toward the Accurate Identification of Network Applications.
PAM 2005: 41-54 |
| 79 | EE | Andrew W. Moore,
Denis Zuev:
Internet traffic classification using bayesian analysis techniques.
SIGMETRICS 2005: 50-60 |
| 78 | EE | David L. Buckeridge,
Howard Burkom,
Murray Campbell,
William R. Hogan,
Andrew W. Moore:
Algorithms for rapid outbreak detection: a research synthesis.
Journal of Biomedical Informatics 38(2): 99-113 (2005) |
| 77 | EE | 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.
Journal of Machine Learning Research 6: 1961-1998 (2005) |
| 76 | EE | Purnamrita Sarkar,
Andrew W. Moore:
Dynamic social network analysis using latent space models.
SIGKDD Explorations 7(2): 31-40 (2005) |
| 2004 |
|---|
| 75 | EE | Daniel B. Neill,
Andrew W. Moore:
Rapid detection of significant spatial clusters.
KDD 2004: 256-265 |
| 74 | EE | Brigham Anderson,
Andrew W. Moore,
Andrew Connolly,
Robert Nichol:
Fast nonlinear regression via eigenimages applied to galactic morphology.
KDD 2004: 40-48 |
| 73 | EE | Kaustav Das,
Andrew W. Moore,
Jeff G. Schneider:
Belief state approaches to signaling alarms in surveillance systems.
KDD 2004: 539-544 |
| 72 | EE | Ting Liu,
Ke Yang,
Andrew W. Moore:
The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data.
KDD 2004: 629-634 |
| 71 | EE | Dan Pelleg,
Andrew W. Moore:
Active Learning for Anomaly and Rare-Category Detection.
NIPS 2004 |
| 70 | EE | Ting Liu,
Andrew W. Moore,
Alexander G. Gray,
Ke Yang:
An Investigation of Practical Approximate Nearest Neighbor Algorithms.
NIPS 2004 |
| 69 | EE | Daniel B. Neill,
Andrew W. Moore,
Francisco Pereira,
Tom M. Mitchell:
Detecting Significant Multidimensional Spatial Clusters.
NIPS 2004 |
| 68 | EE | Andrew W. Moore:
An implementation-based comparison of Measurement-Based Admission Control algorithms.
J. High Speed Networks 13(2): 87-102 (2004) |
| 2003 |
|---|
| 67 | EE | Jeremy Kubica,
Andrew W. Moore:
Probabilistic Noise Identification and Data Cleaning.
ICDM 2003: 131-138 |
| 66 | EE | Jeremy Kubica,
Andrew W. Moore,
Jeff G. Schneider:
Tractable Group Detection on Large Link Data Sets.
ICDM 2003: 573-576 |
| 65 | | 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: 392-399 |
| 64 | | Andrew W. Moore,
Weng-Keen Wong:
Optimal Reinsertion: A New Search Operator for Accelerated and More Accurate Bayesian Network Structure Learning.
ICML 2003: 552-559 |
| 63 | | Weng-Keen Wong,
Andrew W. Moore,
Gregory F. Cooper,
Michael M. Wagner:
Bayesian Network Anomaly Pattern Detection for Disease Outbreaks.
ICML 2003: 808-815 |
| 62 | EE | Daniel B. Neill,
Andrew W. Moore:
A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters.
NIPS 2003 |
| 61 | EE | Ting Liu,
Andrew W. Moore,
Alexander G. Gray:
Efficient Exact k-NN and Nonparametric Classification in High Dimensions.
NIPS 2003 |
| 60 | EE | Alexander G. Gray,
Andrew W. Moore:
Nonparametric Density Estimation: Toward Computational Tractability.
SDM 2003 |
| 2002 |
|---|
| 59 | | Weng-Keen Wong,
Andrew W. Moore,
Gregory F. Cooper,
Michael M. Wagner:
Rule-Based Anomaly Pattern Detection for Detecting Disease Outbreaks.
AAAI/IAAI 2002: 217-223 |
| 58 | | Jeremy Kubica,
Andrew W. Moore,
Jeff G. Schneider,
Yiming Yang:
Stochastic Link and Group Detection.
AAAI/IAAI 2002: 798- |
| 57 | EE | Amitabh Chaudhary,
Alexander S. Szalay,
Andrew W. Moore:
Very Fast Outlier Detection in Large Multidimensional Data Sets.
DMKD 2002 |
| 56 | EE | Dan Pelleg,
Andrew W. Moore:
Using Tarjan's Red Rule for Fast Dependency Tree Construction.
NIPS 2002: 801-808 |
| 55 | | Scott Davies,
Andrew W. Moore:
Interpolating Conditional Density Trees.
UAI 2002: 119-127 |
| 54 | | Andrew W. Moore,
Jeff G. Schneider:
Real-valued All-Dimensions Search: Low-overhead Rapid Searching over Subsets of Attributes.
UAI 2002: 360-369 |
| 53 | EE | Malcolm J. A. Strens,
Andrew W. Moore:
Policy Search using Paired Comparisons.
Journal of Machine Learning Research 3: 921-950 (2002) |
| 52 | | Rémi Munos,
Andrew W. Moore:
Variable Resolution Discretization in Optimal Control.
Machine Learning 49(2-3): 291-323 (2002) |
| 2001 |
|---|
| 51 | | Dan Pelleg,
Andrew W. Moore:
Mixtures of Rectangles: Interpretable Soft Clustering.
ICML 2001: 401-408 |
| 50 | | Peter Sand,
Andrew W. Moore:
Repairing Faulty Mixture Models using Density Estimation.
ICML 2001: 457-464 |
| 49 | | Malcolm J. A. Strens,
Andrew W. Moore:
Direct Policy Search using Paired Statistical Tests.
ICML 2001: 545-552 |
| 48 | EE | 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: 655-665 |
| 2000 |
|---|
| 47 | EE | 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: 137-149 |
| 46 | | Brigham S. Anderson,
Andrew W. Moore,
David Cohn:
A Nonparametric Approach to Noisy and Costly Optimization.
ICML 2000: 17-24 |
| 45 | | Paul Komarek,
Andrew W. Moore:
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets.
ICML 2000: 495-502 |
| 44 | | Rémi Munos,
Andrew W. Moore:
Rates of Convergence for Variable Resolution Schemes in Optimal Control.
ICML 2000: 647-654 |
| 43 | | Dan Pelleg,
Andrew W. Moore:
X-means: Extending K-means with Efficient Estimation of the Number of Clusters.
ICML 2000: 727-734 |
| 42 | | Andrew W. Moore,
Jeff G. Schneider,
Justin A. Boyan,
Mary S. Lee:
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions.
ICRA 2000: 4096- |
| 41 | | Alexander G. Gray,
Andrew W. Moore:
`N-Body' Problems in Statistical Learning.
NIPS 2000: 521-527 |
| 40 | EE | Scott Davies,
Andrew W. Moore:
Mix-nets: Factored Mixtures of Gaussians in Bayesian Networks with Mixed Continuous And Discrete Variables.
UAI 2000: 168-175 |
| 39 | EE | Andrew W. Moore:
The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data.
UAI 2000: 397-405 |
| 38 | EE | Justin A. Boyan,
Andrew W. Moore:
Learning Evaluation Functions to Improve Optimization by Local Search.
Journal of Machine Learning Research 1: 77-112 (2000) |
| 1999 |
|---|
| 37 | | Jeff G. Schneider,
Weng-Keen Wong,
Andrew W. Moore,
Martin A. Riedmiller:
Distributed Value Functions.
ICML 1999: 371-378 |
| 36 | | Andrew W. Moore,
Leemon C. Baird III,
Leslie Pack Kaelbling:
Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs.
IJCAI 1999: 1316-1323 |
| 35 | | Rémi Munos,
Andrew W. Moore:
Variable Resolution Discretization for High-Accuracy Solutions of Optimal Control Problems.
IJCAI 1999: 1348-1355 |
| 34 | EE | Dan Pelleg,
Andrew W. Moore:
Accelerating Exact k-means Algorithms with Geometric Reasoning.
KDD 1999: 277-281 |
| 33 | EE | Scott Davies,
Andrew W. Moore:
Bayesian Networks for Lossless Dataset Compression.
KDD 1999: 387-391 |
| 1998 |
|---|
| 32 | | Justin A. Boyan,
Andrew W. Moore:
Learning Evaluation Functions for Global Optimization and Boolean Satisfiability.
AAAI/IAAI 1998: 3-10 |
| 31 | | Scott Davies,
Andrew Y. Ng,
Andrew W. Moore:
Applying Online Search Techniques to Continuous-State Reinforcement Learning.
AAAI/IAAI 1998: 753-760 |
| 30 | | Andrew W. Moore,
Jeff G. Schneider,
Justin A. Boyan,
Mary S. Lee:
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions.
ICML 1998: 386-394 |
| 29 | | Jeff G. Schneider,
Justin A. Boyan,
Andrew W. Moore:
Value Function Based Production Scheduling.
ICML 1998: 522-530 |
| 28 | | Brigham S. Anderson,
Andrew W. Moore:
ADtrees for Fast Counting and for Fast Learning of Association Rules.
KDD 1998: 134-138 |
| 27 | EE | Rémi Munos,
Andrew W. Moore:
Barycentric Interpolators for Continuous Space and Time Reinforcement Learning.
NIPS 1998: 1024-1030 |
| 26 | EE | Andrew W. Moore:
Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees.
NIPS 1998: 543-549 |
| 25 | EE | Leemon C. Baird III,
Andrew W. Moore:
Gradient Descent for General Reinforcement Learning.
NIPS 1998: 968-974 |
| 24 | EE | Andrew W. Moore,
Mary S. Lee:
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets
CoRR cs.AI/9803102: (1998) |
| 23 | EE | Andrew W. Moore,
Mary S. Lee:
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets.
J. Artif. Intell. Res. (JAIR) 8: 67-91 (1998) |
| 1997 |
|---|
| 22 | | Andrew W. Moore,
Jeff G. Schneider,
Kan Deng:
Efficient Locally Weighted Polynomial Regression Predictions.
ICML 1997: 236-244 |
| 21 | | Christopher G. Atkeson,
Andrew W. Moore,
Stefan Schaal:
Locally Weighted Learning.
Artif. Intell. Rev. 11(1-5): 11-73 (1997) |
| 20 | | Oded Maron,
Andrew W. Moore:
The Racing Algorithm: Model Selection for Lazy Learners.
Artif. Intell. Rev. 11(1-5): 193-225 (1997) |
| 19 | | Christopher G. Atkeson,
Andrew W. Moore,
Stefan Schaal:
Locally Weighted Learning for Control.
Artif. Intell. Rev. 11(1-5): 75-113 (1997) |
| 1996 |
|---|
| 18 | | Andrew W. Moore:
Reinforcement Learning in Factories: The Auton Project (Abstract).
ICML 1996: 556 |
| 17 | | Justin A. Boyan,
Andrew W. Moore:
Learning Evaluation Functions for Large Acyclic Domains.
ICML 1996: 63-70 |
| 16 | EE | Leslie Pack Kaelbling,
Michael L. Littman,
Andrew W. Moore:
Reinforcement Learning: A Survey
CoRR cs.AI/9605103: (1996) |
| 15 | | Andrew W. Moore,
A. J. McGregor,
Jim W. Breen:
A Comparison of System Monitoring Methods, Passive Network Monitoring and Kernel Instrumentation.
Operating Systems Review 30(1): 16-38 (1996) |
| 1995 |
|---|
| 14 | | Kan Deng,
Andrew W. Moore:
Multiresolution Instance-Based Learning.
IJCAI 1995: 1233-1242 |
| 13 | EE | Andrew W. Moore,
Jeff G. Schneider:
Memory-based Stochastic Optimization.
NIPS 1995: 1066-1072 |
| 12 | | Andrew W. Moore,
Christopher G. Atkeson:
The Parti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces.
Machine Learning 21(3): 199-233 (1995) |
| 1994 |
|---|
| 11 | | Andrew W. Moore,
Mary S. Lee:
Efficient Algorithms for Minimizing Cross Validation Error.
ICML 1994: 190-198 |
| 10 | EE | Justin A. Boyan,
Andrew W. Moore:
Generalization in Reinforcement Learning: Safely Approximating the Value Function.
NIPS 1994: 369-376 |
| 1993 |
|---|
| 9 | EE | Thomas G. Dietterich,
Dietrich Wettschereck,
Christopher G. Atkeson,
Andrew W. Moore:
Memory-Based Methods for Regression and Classification.
NIPS 1993: 1165-1166 |
| 8 | EE | Oded Maron,
Andrew W. Moore:
Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation.
NIPS 1993: 59-66 |
| 7 | EE | Andrew W. Moore:
The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces.
NIPS 1993: 711-718 |
| 6 | | Andrew W. Moore,
Christopher G. Atkeson:
Prioritized Sweeping: Reinforcement Learning With Less Data and Less Time.
Machine Learning 13: 103-130 (1993) |
| 1992 |
|---|
| 5 | EE | Andrew W. Moore,
Christopher G. Atkeson:
Memory-Based Reinforcement Learning: Efficient Computation with Prioritized Sweeping.
NIPS 1992: 263-270 |
| 1991 |
|---|
| 4 | | Andrew W. Moore:
Variable Resolution Dynamic Programming.
ML 1991: 333-337 |
| 3 | EE | Andrew W. Moore:
Fast, Robust Adaptive Control by Learning only Forward Models.
NIPS 1991: 571-578 |
| 1990 |
|---|
| 2 | | Andrew W. Moore:
Acquisition of Dynamic Control Knowledge for a Robotic Manipulator.
ML 1990: 244-252 |
| 1 | EE | Andrew W. Moore,
John Allman,
Geoffrey Fox,
Rodney M. Goodman:
A VLSI Neural Network for Color Constancy.
NIPS 1990: 370-376 |
