ISOLA
2010
Springer
13 years 10 months ago
2010
Springer
Latest results of statistical learning theory have provided techniques such us pattern analysis and relational learning, which help in modeling system behavior, e.g. the semantics ...
CORR
2010
Springer
13 years 11 months ago
2010
Springer
We develop a theory of online learning by defining several complexity measures. Among them are analogues of Rademacher complexity, covering numbers and fatshattering dimension fro...
IJCV
2000
13 years 11 months ago
2000
In this paper we first overview the main concepts of Statistical Learning Theory, a framework in which learning from examples can be studied in a principled way. We then briefly di...
JAIR
2006
13 years 11 months ago
2006
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
GECCO
2005
Springer
14 years 5 months ago
2005
Springer
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
CCS
2007
ACM
14 years 5 months ago
2007
ACM
Keystroke typing characteristics is considered as one of the important biometric features that can be used to protect users against malicious attacks. In this paper we propose a s...
EUROGP
2009
Springer
14 years 6 months ago
2009
Springer
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in GP from the perspec...