Spectral Graph Transducer(SGT) is one of the superior graph-based transductive learning methods for classification.
A transcription factor transduction-based method for directly converting fibroblasts into neuronal cells (or induced neurons ) was first reported in 2010.
Spectral Graph Transducer(SGT) is one of the superior graph-based transductive learning methods for classification.
Spectral Graph Transducer (SGT) is one of the superior graph-based transductive learning methods for classification.
Signal transduction to and from adhesion molecules.
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Each step of the transduction generates either a substitution pair ha, bi, a deletion pair ha, ǫi, an insertion pair hǫ, bi, or the distinguished termination symbol # according to a probability function δ : E ∪ {#} → [0, 1].
Learning string edit distance
Our interpretation of string edit distance as a stochastic transduction naturally leads to the following two string distances.
Learning string edit distance
T , yV ), which we call the Viterbi edit The ﬁrst transduction distance dv distance , is the negative logarithm of the probability of the most likely edit sequence for the string pair hxT , yV i.
Learning string edit distance
If the most likely edit sequence for hxT , yV i is signiﬁcantly more likely than any of the other edit sequences, then the two transduction distances will be nearly equal.
Learning string edit distance
Unlike the classic edit distance dc (φ, φ), our two transduction distances are never zero unless they are inﬁnite for all other string pairs.
Learning string edit distance
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