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HOCT: A Highly Scalable Algorithm for Training Linear CRF on Modern Hardware

HOCT: A Highly Scalable Algorithm for Training Linear CRF on Modern Hardware. presented by Tianyuan Chen. Introduction. Conditional random fields (CRFs) are probabilistic models for segmenting and labeling sequential data. They offer many advantages over other models.

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212 views • 12 slides

Revisiting Output Coding for Sequential Supervised Learning

Revisiting Output Coding for Sequential Supervised Learning. Guohua Hao & Alan Fern School of Electrical Engineering and Computer Science Oregon State University Corvallis, OR, U.S.A. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A A A A A.

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234 views • 12 slides

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Crf training - PowerPoint PPT Presentation

HOCT: A Highly Scalable Algorithm for Training Linear CRF on Modern Hardware

Revisiting Output Coding for Sequential Supervised Learning