Ira Assent

Learning Representations for Outlier Detection on a Budget

2015 · arXiv (Cornell University)

The problem of detecting a small number of outliers in a large dataset is an important task in many fields from fraud detection to high-energy physics. Two approaches have emerged to tackle this problem: unsupervised …

Unsupervised Abbreviation Disambiguation Contextual disambiguation using word embeddings

2019 · arXiv (Cornell University)

Abbreviations often have several distinct meanings, often making their use in text ambiguous. Expanding them to their intended meaning in context is important for Machine Reading tasks such as document search, recommendation and question answering. …

Active Learning of SVDD Hyperparameter Values

2020

Support Vector Data Description (SVDD) is a popular one-class classifier, and well-suited for outlier detection. However, the effectiveness of SVDD depends on selecting good hyperparameter values - a difficult problem that has received significant attention …