Search Results for author:
Found 3 papers, 0 papers with code
Surpassing GPT-4 Medical Coding with a Two-Stage Approach
Recent advances in large language models (LLMs) show potential for clinical applications, such as clinical decision support and trial recommendations.
Feature Selection for classification of hyperspectral data by minimizing a tight bound on the VC dimension
Hyperspectral data consists of large number of features which require sophisticated analysis to be extracted.
Learning a Fuzzy Hyperplane Fat Margin Classifier with Minimum VC dimension
The Vapnik-Chervonenkis (VC) dimension measures the complexity of a learning machine, and a low VC dimension leads to good generalization.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
