: Markov models have been proposed for the classification of DNA-motifs using generative approaches for parameter learning. Here, we propose to apply the discriminative paradigm fo...
Jan Grau, Jens Keilwagen, Alexander E. Kel, Ivo Gr...
Near-synonyms are useful knowledge resources for many natural language applications such as query expansion for information retrieval (IR) and paraphrasing for text generation. Ho...
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
We describe in this paper an advanced protocol for the discrimination and the classification of neuronal spike waveforms within multichannel electrophysiological recordings. Sparse...
Vincent Vigneron, Hsin Chen, Yen-Tai Chen, Hsin-Yi...