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09/07/2023
Random Expert Sampling for Deep Learning Segmentation of Acute Ischemic Stroke on Non-contrast CT
Purpose: Multi-expert deep learning training methods to automatically qu...
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11/24/2022
Non-inferiority of Deep Learning Model to Segment Acute Stroke on Non-contrast CT Compared to Neuroradiologists
Purpose: To develop a deep learning model to segment the acute ischemic ...
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09/26/2022
Evaluation of Medical Image Segmentation Models for Uncertain, Small or Empty Reference Annotations
Performance metrics for medical image segmentation models are used to me...
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01/12/2022
On the Statistical Complexity of Sample Amplification
Given n i.i.d. samples drawn from an unknown distribution P, when is it ...
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02/24/2020
Learning From Strategic Agents: Accuracy, Improvement, and Causality
In many predictive decision-making scenarios, such as credit scoring and...
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08/31/2019
Near-optimal Approximate Discrete and Continuous Submodular Function Minimization
In this paper we provide improved running times and oracle complexities ...
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07/18/2019
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
We consider the problem of computing the maximum likelihood multivariate...
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04/26/2019
Sample Amplification: Increasing Dataset Size even when Learning is Impossible
Given data drawn from an unknown distribution, D, to what extent is it p...
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11/08/2018