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Should Machine Learning Models Report to Us When They Are Clueless?



Roozbeh Yousefzadeh , Xuenan Cao


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Over-parameterization: A Necessary Condition for Models that Extrapolate



Roozbeh Yousefzadeh


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Deep Learning Generalization, Extrapolation, and Over-parameterization



Roozbeh Yousefzadeh

* Abstract accepted and presented at the Workshop on Theory of Over-parameterized Machine Learning, April 2021. arXiv admin note: text overlap with arXiv:2101.09849 

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Decision boundaries and convex hulls in the feature space that deep learning functions learn from images



Roozbeh Yousefzadeh


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To what extent should we trust AI models when they extrapolate?



Roozbeh Yousefzadeh , Xuenan Cao


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Community Detection in Medical Image Datasets: Using Wavelets and Spectral Methods



Roozbeh Yousefzadeh


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A Homotopy Algorithm for Optimal Transport



Roozbeh Yousefzadeh

* OPT2020: 12th Annual Workshop on Optimization for Machine Learning 

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Extrapolation Frameworks in Cognitive Psychology Suitable for Study of Image Classification Models



Roozbeh Yousefzadeh , Jessica A. Mollick

* 1st Workshop on Human and Machine Decisions (WHMD 2021) at NeurIPS 2021 

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Federated Learning without Revealing the Decision Boundaries



Roozbeh Yousefzadeh


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