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131
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PRL
2010
158views more  PRL 2010»
15 years 25 days ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain
ML
2002
ACM
123views Machine Learning» more  ML 2002»
15 years 2 months ago
Feature Generation Using General Constructor Functions
Most classification algorithms receive as input a set of attributes of the classified objects. In many cases, however, the supplied set of attributes is not sufficient for creatin...
Shaul Markovitch, Dan Rosenstein
NIPS
2004
15 years 3 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
165
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PRESENCE
2008
185views more  PRESENCE 2008»
15 years 2 months ago
Pilot Evaluation Study of a Virtual Paracentesis Simulator for Skill Training and Assessment: The Beneficial Effect of Haptic Di
Effective, real-time training of health care professionals in invasive procedures is a challenging task. Furthermore, assessing in practice the acquisition of the dexterity and sk...
Costas S. Tzafestas, Kostas Birbas, Yiannis Koumpo...
124
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COLT
2007
Springer
15 years 8 months ago
Resource-Bounded Information Gathering for Correlation Clustering
We present a new class of problems, called resource-bounded information gathering for correlation clustering. Our goal is to perform correlation clustering under circumstances in w...
Pallika Kanani, Andrew McCallum