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» Clustering with Constrained Similarity Learning
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COLING
2010
13 years 2 months ago
Semi-supervised Semantic Pattern Discovery with Guidance from Unsupervised Pattern Clusters
We present a simple algorithm for clustering semantic patterns based on distributional similarity and use cluster memberships to guide semi-supervised pattern discovery. We apply ...
Ang Sun, Ralph Grishman
CLA
2007
13 years 9 months ago
Policies Generalization in Reinforcement Learning using Galois Partitions Lattices
The generalization of policies in reinforcement learning is a main issue, both from the theoretical model point of view and for their applicability. However, generalizing from a se...
Marc Ricordeau, Michel Liquiere
ILP
2003
Springer
14 years 25 days ago
Disjunctive Learning with a Soft-Clustering Method
In the case of concept learning from positive and negative examples, it is rarely possible to find a unique discriminating conjunctive rule; in most cases, a disjunctive descripti...
Guillaume Cleuziou, Lionel Martin, Christel Vrain
ISCAS
2006
IEEE
143views Hardware» more  ISCAS 2006»
14 years 1 months ago
Dynamic computation in a recurrent network of heterogeneous silicon neurons
Abstract—We describe a neuromorphic chip with a twolayer excitatory-inhibitory recurrent network of spiking neurons that exhibits localized clusters of neural activity. Unlike ot...
Paul Merolla, Kwabena Boahen
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 18 days ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer