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ICML
2000
IEEE
13 years 10 months ago
Lightweight Rule Induction
We propose a new rule induction algorithm for solving classification problems via probability estimation. The main advantage of decision rules is their simplicity and good interp...
Sholom M. Weiss, Nitin Indurkhya
ICML
2000
IEEE
13 years 10 months ago
Mutual Information in Learning Feature Transformations
We present feature transformations useful for exploratory data analysis or for pattern recognition. Transformations are learned from example data sets by maximizing the mutual inf...
Kari Torkkola, William M. Campbell
ICML
2000
IEEE
13 years 10 months ago
Using Knowledge to Speed Learning: A Comparison of Knowledge-based Cascade-correlation and Multi-task Learning
Cognitive modeling with neural networks unrealistically ignores the role of knowledge in learning by starting from random weights. It is likely that effective use of knowledge by ...
Thomas R. Shultz, François Rivest
ICML
2000
IEEE
13 years 10 months ago
A Bayesian Framework for Reinforcement Learning
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
Malcolm J. A. Strens
ICML
2000
IEEE
13 years 10 months ago
Using Learning by Discovery to Segment Remotely Sensed Images
In this paper, we describe our research in computer-aided image analysis. We have incorporated machine learning methodologies with traditional image processing to perform unsuperv...
Leen-Kiat Soh, Costas Tsatsoulis
ICML
2000
IEEE
13 years 10 months ago
Discriminative Reranking for Natural Language Parsing
This paper considers approaches which rerank the output of an existing probabilistic parser. The base parser produces a set of candidate parses for each input sentence, with assoc...
Michael Collins
ICML
2000
IEEE
14 years 7 months ago
Solving the Multiple-Instance Problem: A Lazy Learning Approach
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
Jun Wang, Jean-Daniel Zucker
ICML
2000
IEEE
14 years 7 months ago
Enhancing the Plausibility of Law Equation Discovery
Takashi Washio, Hiroshi Motoda, Yuji Niwa
ICML
2000
IEEE
14 years 7 months ago
Clustering with Instance-level Constraints
Clustering algorithms conduct a search through the space of possible organizations of a data set. In this paper, we propose two types of instance-level clustering constraints ? mu...
Kiri Wagstaff, Claire Cardie
ICML
2000
IEEE
14 years 7 months ago
Discovering Homogeneous Regions in Spatial Data through Competition
If all features causing heterogeneity were observed, a mixture of experts approach (Jacobs et al., 1991) is likely to be superior to using a single model. When unobserved or very n...
Slobodan Vucetic, Zoran Obradovic