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* | 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 |