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» Generalization Improvement in Multi-Objective Learning
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ICML
1994
IEEE
15 years 4 months ago
Greedy Attribute Selection
Many real-world domains bless us with a wealth of attributes to use for learning. This blessing is often a curse: most inductive methods generalize worse given too many attributes...
Rich Caruana, Dayne Freitag
NECO
2007
150views more  NECO 2007»
14 years 12 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
112
Voted
ATAL
2008
Springer
15 years 2 months ago
A statistical relational model for trust learning
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
Achim Rettinger, Matthias Nickles, Volker Tresp
134
Voted
JAIR
2002
163views more  JAIR 2002»
15 years 4 days ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 26 days ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...