Blending Learning and Inference in Conditional Random Fields

By Tamir Hazan, Alexander Gerhard Schwing, Raquel Urtasun. 2016

9 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Giuseppe Marra
2. Colin Graber
3. Francesco Giannini
4. Ofer Meshi
5. Alexander Gerhard Schwing
6. Marco Gori
7. Michelangelo Diligenti
8. Abhinav Kumar Gupta

Citations in the corpus

• Integrating Learning and Reasoning with Deep Logic Models (2019, background): “Blending symbolic and sub-symbolic approaches is one of the most challenging open problem in AI and, recently, a lot of works, often referred as neuro-symbolic approaches [10], have been proposed by several authors [6, 14, 22, 27].”
• Deep Structured Prediction with Nonlinear Output Transformations (2018, methodology): “To simplify this, we follow the derivation in [18, 9] by dualizing the LP relaxation problem to convert maximization over X into a minimization over dual variables μ.”