We propose a high-performance cascaded hybrid model for Chinese NER. Firstly, we use Boosting, a standard and theoretically wellfounded machine learning method to combine a set of...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
Background: One of the challenges of bioinformatics remains the recognition of short signal sequences in genomic DNA such as donor or acceptor splice sites, splicing enhancers or ...
Jens Keilwagen, Jan Grau, Stefan Posch, Ivo Grosse
—A Neural integrated Fuzzy conTroller (NiF-T) which integrates the fuzzy logic representation of human knowledge with the learning capability of neural networks is developed for ...
We propose a new integrated approach based on Markov logic networks (MLNs), an effective combination of probabilistic graphical models and firstorder logic for statistical relatio...