Abstract. We study various ensemble methods for hybrid neural networks. The hybrid networks are composed of radial and projection units and are trained using a deterministic algori...
The use of modified Real Adaboost ensembles by applying weighted emphasis on erroneous and critical (near the classification boundary) has been shown to lead to improved designs, ...
We present a data-driven variant of the LR algorithm for dependency parsing, and extend it with a best-first search for probabilistic generalized LR dependency parsing. Parser act...
Regression Error Characteristic (REC) analysis is a technique for evaluation and comparison of regression models that facilitates the visualization of the performance of many regre...
We propose a general framework for performing independent component analysis (ICA) which relies on ensemble learning and linear response theory known from statistical physics. We ...