Hidden Markov Support Vector Machines

  title={Hidden Markov Support Vector Machines},
  author={Yasemin Altun and Ioannis Tsochantaridis and Thomas Hofmann},
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines and Hidden Markov Models which we call Hidden Markov Support Vector Machine. The proposed architecture handles dependencies between neighboring labels using Viterbi decoding. In contrast to standard HMM training, the learning procedure is discriminative and is based on a maximum/soft margin criterion. Compared to… CONTINUE READING
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