Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using akly-labeled data. GE fits model parameters by favoring models that match certain expectation constraints, such as marginal label distributions, on the unlabeled data.  shows how to apply generalized expectation criteria to two classes of parametric models: maximum entropy models and conditional random fields. Experimental results demonstrate accuracy improvements over supervised training and a number of other state-of-the-art semi-supervised learning methods for these models.
['Gideon S. Mann', 'Andrew McCallum']
I am writing a research paper on a idea Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data
[{"from": "human", "value": "I am writing a research paper on a idea Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using akly-labeled data. GE fits model parameters by favoring models that match certain expectation constraints, such as marginal label distributions, on the unlabeled data.  shows how to apply generalized expectation criteria to two classes of parametric models: maximum entropy models and conditional random fields. Experimental results demonstrate accuracy improvements over supervised training and a number of other state-of-the-art semi-supervised learning methods for these models."}]