Search Results for author: Andreas Stephan

Found 5 papers, 3 papers with code

WeaNF”:" Weak Supervision with Normalizing Flows

no code implementations RepL4NLP (ACL) 2022 Andreas Stephan, Benjamin Roth

In this work, we explore a novel direction of generative modeling for weak supervision”:" Instead of modeling the output of the annotation process (the labeling function matches), we generatively model the input-side data distributions (the feature space) covered by labeling functions.

SepLL: Separating Latent Class Labels from Weak Supervision Noise

1 code implementation25 Oct 2022 Andreas Stephan, Vasiliki Kougia, Benjamin Roth

In this work, we provide a method for learning from weak labels by separating two types of complementary information associated with the labeling functions: information related to the target label and information specific to one labeling function only.

text-classification Text Classification

WeaNF: Weak Supervision with Normalizing Flows

2 code implementations28 Apr 2022 Andreas Stephan, Benjamin Roth

In this work, we explore a novel direction of generative modeling for weak supervision: Instead of modeling the output of the annotation process (the labeling function matches), we generatively model the input-side data distributions (the feature space) covered by labeling functions.

Knodle: Modular Weakly Supervised Learning with PyTorch

1 code implementation ACL (RepL4NLP) 2021 Anastasiia Sedova, Andreas Stephan, Marina Speranskaya, Benjamin Roth

Strategies for improving the training and prediction quality of weakly supervised machine learning models vary in how much they are tailored to a specific task or integrated with a specific model architecture.

BIG-bench Machine Learning Sentiment Analysis +1

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