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NULL SPACE ANALYSIS OF NEURAL NETWORKS PRESENTED AT ICML

July 17, 2020

Congratulations to our labmates, Matt Cook, Alina Zare and Paul Gader for presenting at the 37th International Conference on Machine Learning (ICML) Workshop on Uncertainty and Robustness in Machine Learning! Their paper, titled “Outlier Detection through Null Space Analysis of Neural Networks”, introduces a novel method for detecting outliers in a set of data. Matt will […]

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OUTLIER DETECTION THROUGH NULL SPACE ANALYSIS OF NEURAL NETWORKS

July 17, 2020

Abstract: Many machine learning classification systems lack competency awareness. Specifically, many systems lack the ability to identify when outliers (e.g., samples that are distinct from and not represented in the training data distribution) are being presented to the system. The ability to detect outliers is of practical significance since it can help the system behave […]

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