4591 search results - page 390 / 919 » Learning from Dyadic Data |
155
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ICANN
2001
Springer
2001
Springer
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
15 years 11 months ago
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
183
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ACSAC
1999
IEEE
15 years 11 months ago
1999
IEEE
Differentiating anomalous network activity from normal network traffic is difficult and tedious. A human analyst must search through vast amounts of data to find anomalous sequenc...
174
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AI
1998
Springer
15 years 11 months ago
1998
Springer
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
349
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NIPS
2008
15 years 8 months ago
2008
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
197
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IICAI
2003
15 years 8 months ago
2003
Abstract. We introduce a new genetic algorithm approach for learning a Bayesian network structure from data. Our method is capable of learning over all node orderings and structure...