Invention Grant
- Patent Title: Sparse higher-order Markov random field
- Patent Title (中): 稀疏高阶马尔可夫随机场
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Application No.: US13908715Application Date: 2013-06-03
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Publication No.: US09183503B2Publication Date: 2015-11-10
- Inventor: Renqiang Min , Yanjun Qi
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: US NJ Princeton
- Assignee: NEC Laboratories America, Inc.
- Current Assignee: NEC Laboratories America, Inc.
- Current Assignee Address: US NJ Princeton
- Agent Joseph Kolodka
- Main IPC: G06N5/02
- IPC: G06N5/02

Abstract:
Systems and methods are provided for identifying combinatorial feature interactions, including capturing statistical dependencies between categorical variables, with the statistical dependencies being stored in a computer readable storage medium. A model is selected based on the statistical dependencies using a neighborhood estimation strategy, with the neighborhood estimation strategy including generating sets of arbitrarily high-order feature interactions using at least one rule forest and optimizing one or more likelihood functions. A damped mean-field approach is applied to the model to obtain parameters of a Markov random field (MRF); a sparse high-order semi-restricted MRF is produced by adding a hidden layer to the MRF; indirect long-range dependencies between feature groups are modeled using the sparse high-order semi-restricted MRF; and a combinatorial dependency structure between variables is output.
Public/Granted literature
- US20130325786A1 SPARSE HIGHER-ORDER MARKOV RANDOM FIELD Public/Granted day:2013-12-05
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