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Predicting the Performance of Foundation Models via Agreement-on-the-Line
Recently, it was shown that ensembles of neural networks observe the phenomena ``agreement-on-the-line'', which can be leveraged to reliably predict OOD performance without labels.
On Extending Amdahl's law to Learn Computer Performance
To solve this problem, we propose to (1) extend Amdahl's law to accommodate multiple configurable resources into the overall speedup equation, and (2) transform the speedup equation into a multivariable regression problem suitable for machine learning.
Medical Information Retrieval and Interpretation: A Question-Answer based Interaction Model
The Internet has become a very powerful platform where diverse medical information are expressed daily.
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