We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
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...
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensio...
Abstract. We study Winner-Takes-All and rank based Vector Quantization along the lines of the statistical physics of off-line learning. Typical behavior of the system is obtained w...
— A learning machine is called singular if its Fisher information matrix is singular. Almost all learning machines used in information processing are singular, for example, layer...