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Found 5 papers, 1 papers with code
End-to-End Extraction of Structured Information from Business Documents with Pointer-Generator Networks
The predominant approaches for extracting key information from documents resort to classifiers predicting the information type of each word.
Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds
The PAC-Bayesian framework has significantly advanced our understanding of statistical learning, particularly in majority voting methods.
PAC-Bayesian Domain Adaptation Bounds for Multi-view learning
This paper presents a series of new results for domain adaptation in the multi-view learning setting.
A hybrid algorithm for Bayesian network structure learning with application to multi-label learning
Our extensive experiments show that H2PC outperforms MMHC in terms of goodness of fit to new data and quality of the network structure with respect to the true dependence structure of the data.
An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning
We present a novel hybrid algorithm for Bayesian network structure learning, called Hybrid HPC (H2PC).
