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ICDM
2007
IEEE
97views Data Mining» more  ICDM 2007»
15 years 4 months ago
Supervised Learning by Training on Aggregate Outputs
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. We present a new twist on...
David R. Musicant, Janara M. Christensen, Jamie F....
IJCAI
2007
14 years 11 months ago
Online Speed Adaptation Using Supervised Learning for High-Speed, Off-Road Autonomous Driving
The mobile robotics community has traditionally addressed motion planning and navigation in terms of steering decisions. However, selecting the best speed is also important – be...
David Stavens, Gabriel Hoffmann, Sebastian Thrun
JIFS
2008
155views more  JIFS 2008»
14 years 9 months ago
Improving supervised learning performance by using fuzzy clustering method to select training data
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
Donghai Guan, Weiwei Yuan, Young-Koo Lee, Andrey G...
NECO
2006
103views more  NECO 2006»
14 years 9 months ago
Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning
In timing-based neural codes, neurons have to emit action potentials at precise moments in time. We use a supervised learning paradigm to derive a synaptic update rule that optimi...
Jean-Pascal Pfister, Taro Toyoizumi, David Barber,...
IJCAI
2007
14 years 11 months ago
Semi-Supervised Learning of Attribute-Value Pairs from Product Descriptions
We describe an approach to extract attribute-value pairs from product descriptions. This allows us to represent products as sets of such attribute-value pairs to augment product d...
Katharina Probst, Rayid Ghani, Marko Krema, Andrew...