Search Results for author: Mike Izbicki

Found 4 papers, 2 papers with code

Aligning Word Vectors on Low-Resource Languages with Wiktionary

1 code implementation loresmt (COLING) 2022 Mike Izbicki

Aligned word embeddings have become a popular technique for low-resource natural language processing.

Word Embeddings

Multilingual Emoticon Prediction of Tweets about COVID-19

1 code implementation COLING (PEOPLES) 2020 Stefanos Stoikos, Mike Izbicki

Emojis are a widely used tool for encoding emotional content in informal messages such as tweets, and predicting which emoji corresponds to a piece of text can be used as a proxy for measuring the emotional content in the text.

Evaluating Word Embeddings on Low-Resource Languages

no code implementations EMNLP (Eval4NLP) 2020 Nathan Stringham, Mike Izbicki

The analogy task introduced by Mikolov et al. (2013) has become the standard metric for tuning the hyperparameters of word embedding models.

Model Selection Word Embeddings

The Tree Loss: Improving Generalization with Many Classes

no code implementations16 Apr 2022 Yujie Wang, Mike Izbicki

We introduce the tree loss as a drop-in replacement for the cross entropy loss.

Multi-class Classification

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