We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalizatio...
A kernel over the Boolean domain is said to be reflection-invariant, if its value does not change when we flip the same bit in both arguments. (Many popular kernels have this prop...
Thorsten Doliwa, Michael Kallweit, Hans-Ulrich Sim...
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...