May 27, 2017 · Weak Supervision for Semi-supervised Topic Modeling via Word Embeddings · 1 Introduction · 2 Related Work · 3 Methods · 4 Experimental Evaluation · 5 ...
Jul 27, 2017 · Weak Supervision for Semi-Supervised Topic Modeling via Word Embeddings ... Semi-supervised algorithms have been shown to improve the results of ...
This paper proposes a new process, Weak+, suitable for use in semi-supervised topic modeling via matrix factorization, when limited supervision is available.
This paper proposes a new process, Weak+, suitable for use in semi-supervised topic modeling via matrix factorization, when limited supervision is available.
... {Weak Supervision for Semi-Supervised Topic Modeling via Word Embeddings}, year = {2017} }
Weak Supervision for Semi-Supervised Topic Modeling via Word Embeddings. (2017-06-20). Conheady, Gerald. ;. Greene, Derek. Semi-supervised algorithms have been ...
Weak Supervision for Semi-supervised Topic. Modeling via Word Embeddings. Language, Data, and Knowledge. LDK 2017., pages 150–155, 2017. 3. J.P. Cross and D ...
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What is weak supervision in NLP?
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Our method has the flexibility to handle different types of weak supervision and can be easily integrated into existing deep neural models for text ...
Jul 17, 2024 · In this paper, we leverage word similarity data as the weak supervision of our model. Since the word similarity is based on the correlation ( ...
In this work, we proposed supervising Neural Topic Models with weak supervision via informative priors and explored a variety of model posteriors. A careful ...
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