| |
 |      |
                                              |
Note: Links lead to the DBLP on the Web. Andrew W. Moore Jeremy Kubica , Andrew W. Moore, Jeff G. Schneider : Tractable Group Detection on Large Link Data Sets. ICDM 2003 : 573-576 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 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 Weng-Keen Wong , Andrew W. Moore, Gregory F. Cooper , Michael Wagner : Bayesian Network Anomaly Pattern Detection for Disease Outbreaks. ICML 2003 : 808-815 Alexander G. Gray , Andrew W. Moore: Nonparametric Density Estimation: Toward Computational Tractability. SDM 2003 Weng-Keen Wong , Andrew W. Moore, Gregory F. Cooper , Michael Wagner : Rule-Based Anomaly Pattern Detection for Detecting Disease Outbreaks. AAAI/IAAI 2002 : 217-223 Jeremy Kubica , Andrew W. Moore, Jeff G. Schneider , Yiming Yang : Stochastic Link and Group Detection. AAAI/IAAI 2002 : 798- Amitabh Chaudhary , Alexander S. Szalay , Andrew W. Moore: Very Fast Outlier Detection in Large Multidimensional Data Sets. DMKD 2002 Scott Davies , Andrew W. Moore: Interpolating Conditional Density Trees. UAI 2002 : 119-127 Andrew W. Moore, Jeff G. Schneider : Real-valued All-Dimensions Search: Low-overhead Rapid Searching over Subsets of Attributes. UAI 2002 : 360-369 Malcolm J. A. Strens , Andrew W. Moore: Policy Search using Paired Comparisons. Journal of Machine Learning Research 3 : 921-950 (2002) Rémi Munos , Andrew W. Moore: Variable Resolution Discretization in Optimal Control. Machine Learning 49 (2-3): 291-323 (2002) Dan Pelleg , Andrew W. Moore: Mixtures of Rectangles: Interpretable Soft Clustering. ICML 2001 : 401-408 Peter Sand , Andrew W. Moore: Repairing Faulty Mixture Models using Density Estimation. ICML 2001 : 457-464 Malcolm J. A. Strens , Andrew W. Moore: Direct Policy Search using Paired Statistical Tests. ICML 2001 : 545-552 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 Brigham S. Anderson , Andrew W. Moore, David Cohn : A Nonparametric Approach to Noisy and Costly Optimization. ICML 2000 : 17-24 Paul Komarek , Andrew W. Moore: A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets. ICML 2000 : 495-502 Rémi Munos , Andrew W. Moore: Rates of Convergence for Variable Resolution Schemes in Optimal Control. ICML 2000 : 647-654 Dan Pelleg , Andrew W. Moore: X-means: Extending K-means with Efficient Estimation of the Number of Clusters. ICML 2000 : 727-734 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- Alexander G. Gray , Andrew W. Moore: `N-Body' Problems in Statistical Learning. NIPS 2000 : 521-527 Scott Davies , Andrew W. Moore: Mix-nets: Factored Mixtures of Gaussians in Bayesian Networks with Mixed Continuous And Discrete Variables. UAI 2000 : 168-175 Andrew W. Moore: The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data. UAI 2000 : 397-405 Justin A. Boyan , Andrew W. Moore: Learning Evaluation Functions to Improve Optimization by Local Search. Journal of Machine Learning Research 1 : 77-112 (2000) Jeff G. Schneider , Weng-Keen Wong , Andrew W. Moore, Martin A. Riedmiller : Distributed Value Functions. ICML 1999 : 371-378 Andrew W. Moore, Leemon Baird , Leslie Pack Kaelbling : Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs. IJCAI 1999 : 1316-1323 Rémi Munos , Andrew W. Moore: Variable Resolution Discretization for High-Accuracy Solutions of Optimal Control Problems. IJCAI 1999 : 1348-1355 Dan Pelleg , Andrew W. Moore: Accelerating Exact k -means Algorithms with Geometric Reasoning. KDD 1999 : 277-281 Scott Davies , Andrew W. Moore: Bayesian Networks for Lossless Dataset Compression. KDD 1999 : 387-391 Justin A. Boyan , Andrew W. Moore: Learning Evaluation Functions for Global Optimization and Boolean Satisfiability. AAAI/IAAI 1998 : 3-10 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 Jeff G. Schneider , Justin A. Boyan , Andrew W. Moore: Value Function Based Production Scheduling. ICML 1998 : 522-530 Brigham S. Anderson , Andrew W. Moore: ADtrees for Fast Counting and for Fast Learning of Association Rules. KDD 1998 : 134-138 Rémi Munos , Andrew W. Moore: Barycentric Interpolators for Continuous Space and Time Reinforcement Learning. NIPS 1998 : 1024-1030 Andrew W. Moore: Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees. NIPS 1998 : 543-549 Leemon Baird , Andrew W. Moore: Gradient Descent for General Reinforcement Learning. NIPS 1998 : 968-974 Andrew W. Moore, Mary S. Lee : Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets. JAIR 8 : 67-91 (1998) Andrew W. Moore, Jeff G. Schneider , Kan Deng : Efficient Locally Weighted Polynomial Regression Predictions. ICML 1997 : 236-244 Christopher G. Atkeson , Andrew W. Moore, Stefan Schaal : Locally Weighted Learning. Artif. Intell. Rev. 11 (1-5): 11-73 (1997) Oded Maron , Andrew W. Moore: The Racing Algorithm: Model Selection for Lazy Learners. Artif. Intell. Rev. 11 (1-5): 193-225 (1997) Christopher G. Atkeson , Andrew W. Moore, Stefan Schaal : Locally Weighted Learning for Control. Artif. Intell. Rev. 11 (1-5): 75-113 (1997) Andrew W. Moore: Reinforcement Learning in Factories: The Auton Project (Abstract). ICML 1996 : 556 Justin A. Boyan , Andrew W. Moore: Learning Evaluation Functions for Large Acyclic Domains. ICML 1996 : 63-70 Kan Deng , Andrew W. Moore: Multiresolution Instance-Based Learning. IJCAI 1995 : 1233-1242 Andrew W. Moore, Jeff G. Schneider : Memory-based Stochastic Optimization. NIPS 1995 : 1066-1072 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) Andrew W. Moore, Mary S. Lee : Efficient Algorithms for Minimizing Cross Validation Error. ICML 1994 : 190-198 Justin A. Boyan , Andrew W. Moore: Generalization in Reinforcement Learning: Safely Approximating the Value Function. NIPS 1994 : 369-376 Thomas G. Dietterich , Dietrich Wettschereck , Christopher G. Atkeson , Andrew W. Moore: Memory-Based Methods for Regression and Classification. NIPS 1993 : 1165-1166 Oded Maron , Andrew W. Moore: Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation. NIPS 1993 : 59-66 Andrew W. Moore: The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces. NIPS 1993 : 711-718 Andrew W. Moore, Christopher G. Atkeson : Prioritized Sweeping: Reinforcement Learning With Less Data and Less Time. Machine Learning 13 : 103-130 (1993) Andrew W. Moore, Christopher G. Atkeson : Memory-Based Reinforcement Learning: Efficient Computation with Prioritized Sweeping. NIPS 1992 : 263-270 Andrew W. Moore: Variable Resolution Dynamic Programming. ML 1991 : 333-337 Andrew W. Moore: Fast, Robust Adaptive Control by Learning only Forward Models. NIPS 1991 : 571-578 Andrew W. Moore: Acquisition of Dynamic Control Knowledge for a Robotic Manipulator. ML 1990 : 244-252 1 [ 24 ] [ 41 ] 2 [ 4 ] [ 5 ] [ 8 ] [ 11 ] [ 16 ] [ 18 ] 3 [ 21 ] [ 31 ] 4 [ 9 ] [ 14 ] [ 25 ] [ 26 ] [ 27 ] [ 33 ] [ 37 ] 5 [ 50 ] 6 [ 41 ] [ 56 ] 7 [ 52 ] [ 54 ] 8 [ 28 ] [ 35 ] [ 49 ] 9 [ 13 ] [ 19 ] 10 [ 8 ] 11 [ 36 ] [ 53 ] 12 [ 31 ] 13 [ 40 ] 14 [ 51 ] [ 56 ] [ 57 ] 15 [ 10 ] [ 20 ] [ 26 ] [ 37 ] 16 [ 7 ] [ 17 ] 17 [ 23 ] [ 30 ] [ 39 ] [ 46 ] 18 [ 29 ] [ 38 ] [ 45 ] 19 [ 32 ] [ 42 ] 20 [ 44 ] 21 [ 16 ] [ 18 ] 22 [ 12 ] [ 19 ] [ 25 ] [ 26 ] [ 32 ] [ 37 ] [ 42 ] [ 48 ] [ 51 ] [ 56 ] [ 57 ] 23 [ 43 ] [ 47 ] 24 [ 50 ] 25 [ 52 ] [ 54 ] 26 [ 8 ] 27 [ 32 ] [ 52 ] [ 54 ] [ 55 ] 28 [ 51 ]  ©2004 Association for Computing Machinery |
