137 search results - page 19 / 28 » Quantifying the Impact of Learning Algorithm Parameter Tunin... |
CP
2004
Springer
14 years 10 days ago
2004
Springer
This paper presents a new optimization metaheuristic called ID Walk (Intensification/Diversification Walk) that offers advantages for combining simplicity with effectiveness. In ad...
NN
1998
Springer
13 years 8 months ago
1998
Springer
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
CCS
2009
ACM
14 years 3 months ago
2009
ACM
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
ICML
1999
IEEE
14 years 9 months ago
1999
IEEE
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
CRV
2009
IEEE
14 years 3 months ago
2009
IEEE
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...