Finding the State Sequence Maximizing P(O, I vertical bar lambda) on Distributed HMMs with Privacy

Renckes S., Polat H., Oysal Y.

IEEE Symposium on Computational Intelligence in Cyber Security, Tennessee, Amerika Birleşik Devletleri, 30 Mart - 02 Nisan 2009, ss.152-158 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Basıldığı Şehir: Tennessee
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.152-158
  • Anadolu Üniversitesi Adresli: Evet

Özet

Hidden Markov models (HMMs) are widely used by many applications for forecasting purposes. They are increasingly becoming popular models as part of prediction systems in finance, marketing, bio-informatics, speech recognition, signal processing, and so on. Given an HMM, an application of HMMs is to choose a state sequence so that the joint, probability of an observation sequence and a state sequence given the model is maximized. Although this seems an easy task if the model is given, it becomes a challenge when the model is distributed between various parties. Due to privacy,,financial, and legal reasons, the model owners might not want to integrate their split models.