Abstract Details
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Activity Number:
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190
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Type:
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Contributed
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Date/Time:
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Monday, August 5, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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| Abstract - #309871 |
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Title:
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Factoring Hidden State Spaces for HMMs
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Author(s):
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Jordan Rodu*+
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Companies:
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University of Pennsylvania-Wharton
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Keywords:
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Hidden Markov Models ;
Factorial HMM
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Abstract:
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Factorial HMMs provide a mechanism for for increasing the richness in structure of the hidden state space of a traditional HMM, without requiring a huge blow-up in number of hidden states. Taking inspiration from the factorial nature of factorial HMMs, we explore methods to factor a hidden state space to allow for better forecasting while remaining tractable through recent spectral estimation techniques. We apply our methods to financial and medical data.
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Authors who are presenting talks have a * after their name.
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