Exact MAP inference in general higher-order graphical models using linear programming
📰 ArXiv cs.AI
Researchers propose a linear programming approach for exact MAP inference in higher-order graphical models
Action Steps
- Introduce the notion of delta-distribution to simplify the algebraic proof
- Develop a linear programming relaxation approach for exact MAP inference
- Apply the approach to general higher-order graphical models
- Analyze the results and compare with existing methods
Who Needs to Know This
Machine learning researchers and engineers working on graphical models and inference algorithms can benefit from this research, as it provides a new approach for exact MAP inference
Key Insight
💡 Linear programming can be used for exact MAP inference in higher-order graphical models
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📈 Exact MAP inference in higher-order graphical models using linear programming! 💡
Key Takeaways
Researchers propose a linear programming approach for exact MAP inference in higher-order graphical models
Full Article
Title: Exact MAP inference in general higher-order graphical models using linear programming
Abstract:
arXiv:1709.09051v2 Announce Type: replace-cross Abstract: This paper is concerned with the problem of exact MAP inference in general higher-order graphical models by means of a traditional linear programming relaxation approach. In fact, the proof that we have developed in this paper is a rather simple algebraic proof being made straightforward, above all, by the introduction of two novel algebraic tools. Indeed, on the one hand, we introduce the notion of delta-distribution which merely stands
Abstract:
arXiv:1709.09051v2 Announce Type: replace-cross Abstract: This paper is concerned with the problem of exact MAP inference in general higher-order graphical models by means of a traditional linear programming relaxation approach. In fact, the proof that we have developed in this paper is a rather simple algebraic proof being made straightforward, above all, by the introduction of two novel algebraic tools. Indeed, on the one hand, we introduce the notion of delta-distribution which merely stands
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