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» Generation of Attributes for Learning Algorithms
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NIPS
2003
13 years 10 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Stuart Andrews, Thomas Hofmann
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 3 months ago
Generating large-scale neural networks through discovering geometric regularities
Connectivity patterns in biological brains exhibit many repeating motifs. This repetition mirrors inherent geometric regularities in the physical world. For example, stimuli that ...
Jason Gauci, Kenneth O. Stanley
ML
2006
ACM
163views Machine Learning» more  ML 2006»
13 years 9 months ago
Extremely randomized trees
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Pierre Geurts, Damien Ernst, Louis Wehenkel
ICDE
2008
IEEE
182views Database» more  ICDE 2008»
14 years 3 months ago
Two-phase schema matching in real world relational databases
— We propose a new approach to the problem of schema matching in relational databases that merges the hybrid and composite approach of combining multiple individual matching tech...
Nikolaos Bozovic, Vasilis Vassalos
ICML
2010
IEEE
13 years 10 months ago
Finding Planted Partitions in Nearly Linear Time using Arrested Spectral Clustering
We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high pro...
Nader H. Bshouty, Philip M. Long