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Development repository for the STARLinG Lab's webpage. Built wtih Jekyll, jQuery, and the minimal-mistakes Jekyll theme.
BoostSRL: "Boosting for Statistical Relational Learning." A gradient-boosting based approach for learning different types of SRL models.
Knowledge-intensive Gradient Boosting: A unified framework for learning gradient boosted decision trees for regression and classification tasks while leveraging human advice for achieving better performance.
This repository contains code base for the slim version of BoostSRL. Performance wise, they are the same, but differs in the volume of redundant code removed in this slim version
The interface lets experts annotate textual data to help a model
TensorFlow implementation of "Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach"