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KDD
1994
ACM
140views Data Mining» more  KDD 1994»
15 years 6 months ago
A Comparison of Pruning Methods for Relational Concept Learning
Pre-Pruning and Post-Pruning are two standard methods of dealing with noise in concept learning. Pre-Pruning methods are very efficient, while Post-Pruning methods typically are m...
Johannes Fürnkranz
124
Voted
IJCAI
2001
15 years 4 months ago
Learning Procedural Knowledge to Better Coordinate
A fundamental difficulty faced by groups of agents that work together is how to efficiently coordinate their efforts. This paper presents techniques that allow heterogeneous agent...
Andrew Garland, Richard Alterman
94
Voted
SDM
2004
SIAM
123views Data Mining» more  SDM 2004»
15 years 4 months ago
Nonlinear Manifold Learning for Data Stream
There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
Martin H. C. Law, Nan Zhang 0002, Anil K. Jain
99
Voted
AAAI
2000
15 years 4 months ago
Learning the Common Structure of Data
The proliferation of online information sources has accentuated the need for tools that automatically validate and recognize data. We present an efficient algorithm that learns st...
Kristina Lerman, Steven Minton
112
Voted
ICML
2008
IEEE
16 years 3 months ago
A decoupled approach to exemplar-based unsupervised learning
A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by restricting the set of possi...
Gökhan H. Bakir, Sebastian Nowozin