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13 papers · 2 filters
Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches
Siqi Li, Di Miao, Qiming Wu +9
Federated learning (FL) has shown promising potential in safeguarding data privacy in healthcare collaborations. While the term "FL" was originally coined by the engineering commun…
Fast and Interpretable Mortality Risk Scores for Critical Care Patients
Chloe Qinyu Zhu, Muhang Tian, Lesia Semenova +4
Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (…
A Path to Simpler Models Starts With Noise
Lesia Semenova, Harry Chen, Ronald Parr +1
The Rashomon set is the set of models that perform approximately equally well on a given dataset, and the Rashomon ratio is the fraction of all models in a given hypothesis space t…
Why Shallow Networks Struggle to Approximate and Learn High Frequencies
Shijun Zhang, Hongkai Zhao, Yimin Zhong +1
In this work, we present a comprehensive study combining mathematical and computational analysis to explain why a two-layer neural network struggles to handle high frequencies in b…
An Effective Meaningful Way to Evaluate Survival Models
Shi-ang Qi, Neeraj Kumar, Mahtab Farrokh +5
One straightforward metric to evaluate a survival prediction model is based on the Mean Absolute Error (MAE) -- the average of the absolute difference between the time predicted by…
Machine learning with tree tensor networks, CP rank constraints, and tensor dropout
Hao Chen, Thomas Barthel
Tensor networks developed in the context of condensed matter physics try to approximate order- tensors with a reduced number of degrees of freedom that is only polynomial in …