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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 30 / No. 1: Thirtieth AAAI Conference On Artificial Intelligence

Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster

March 8, 2023

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Authors

Jesse Glass

Temple University


Mohamed Ghalwash

Temple University


Milan Vukicevic

University of Belgrade


Zoran Obradovic

Temple University


DOI:

10.1609/aaai.v30i1.10301


Abstract:

Gaussian Conditional Random Fields (GCRF) are atype of structured regression model that incorporatesmultiple predictors and multiple graphs. This isachieved by defining quadratic term feature functions inGaussian canonical form which makes the conditionallog-likelihood function convex and hence allows findingthe optimal parameters by learning from data. In thiswork, the parameter space for the GCRF model is extendedto facilitate joint modelling of positive and negativeinfluences. This is achieved by restricting the modelto a single graph and formulating linear bounds on convexitywith respect to the models parameters. In addition,our formulation for the model using one networkallows calculating gradients much faster than alternativeimplementations. Lastly, we extend the model onestep farther and incorporate a bias term into our linkweight. This bias is solved as part of the convex optimization.Benefits of the proposed model in terms ofimproved accuracy and speed are characterized on severalsynthetic graphs with 2 million links as well as on ahospital admissions prediction task represented as a humandisease-symptom similarity network correspondingto more than 35 million hospitalization records inCalifornia over 9 years.

Topics: AAAI

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HOW TO CITE:

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster Proceedings of the AAAI Conference on Artificial Intelligence, 30 (2016) .

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster AAAI 2016, .

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic (2016). Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster. Proceedings of the AAAI Conference on Artificial Intelligence, 30, .

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic. Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster. Proceedings of the AAAI Conference on Artificial Intelligence, 30 2016 p..

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic. 2016. Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster. "Proceedings of the AAAI Conference on Artificial Intelligence, 30". .

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic. (2016) "Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster", Proceedings of the AAAI Conference on Artificial Intelligence, 30, p.

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic, "Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster", AAAI, p., 2016.

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic. "Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster". Proceedings of the AAAI Conference on Artificial Intelligence, 30, 2016, p..

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic. "Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster". Proceedings of the AAAI Conference on Artificial Intelligence, 30, (2016): .

Jesse Glass|| Mohamed Ghalwash|| Milan Vukicevic|| Zoran Obradovic. Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster. AAAI[Internet]. 2016[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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