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- Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore
- J. Artif. Intell. Res.
- 1996

This paper surveys the eld of reinforcement learning from a computer science perspective It is written to be accessible to researchers familiar with machine learning Both the historical basis of theâ€¦ (More)

- Dan Pelleg, Andrew W. Moore
- ICML
- 2000

Despite its popularity for general clustering, K-means suuers three major shortcomings; it scales poorly computationally, the number of clusters K has to be supplied by the user, and the search isâ€¦ (More)

- Christopher G. Atkeson, Andrew W. Moore, Stefan Schaal
- Artificial Intelligence Review
- 1997

This paper surveys locally weighted learning, a form of lazy learning and memory-based learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothingâ€¦ (More)

- Justin A. Boyan, Andrew W. Moore
- NIPS
- 1994

To appear in G Tesauro D S Touretzky and T K Leen eds Advances in Neural Information Processing Systems MIT Press Cambridge MA A straightforward approach to the curse of dimensionality in reâ€¦ (More)

- Andrew W. Moore
- NIPS
- 1998

Clustering is important in many elds including manufacturing bi ology nance and astronomy Mixture models are a popular approach due to their statistical foundations and EM is a very popular methodâ€¦ (More)

- Christopher G. Atkeson, Andrew W. Moore, Stefan Schaal
- Artificial Intelligence Review
- 1997

Lazy learning methods provide useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of complex systems. This paper surveys ways inâ€¦ (More)

- Leemon C. Baird, Andrew W. Moore
- NIPS
- 1998

Andrew Moore awm@cs.cmu.edu www.cs.cmu.edu/-awm Computer Science Department 5000 Forbes Avenue Carnegie Mellon University Pittsburgh, PA 15213-3891 A simple learning rule is derived, the VAPSâ€¦ (More)

- Ting Liu, Andrew W. Moore, Alexander G. Gray, Ke Yang
- NIPS
- 2004

This paper concerns approximate nearest neighbor searching algorithms, which have become increasingly important, especially in high dimensional perception areas such as computer vision, with dozensâ€¦ (More)

- Andrew W. Moore, Mary S. Lee
- J. Artif. Intell. Res.
- 1998

This paper introduces new algorithms and data st.ruct,ures for quick rounting for machine learning dat.asets. We focus on t,he counting task of constructing contingent:. t.ables, but our approach isâ€¦ (More)

- Dan Pelleg, Andrew W. Moore
- KDD
- 1999

We present new algorithms for the k-means clustering problem. They use the kd-tree data structure to reduce the large number of nearest-neighbor queries issued by the traditional algorithm. Su cientâ€¦ (More)