3 papers
cs.LG2026
A Blended Likelihood Approach for Achieving Fairness Using Naive Bayes
John Arthur Junior, Abdul Lateef Yussif, Maame G. Asante-Mensah +3
Concerns about algorithmic bias and fairness have increased as artificial intelligence has been incorporated into high-stakes decision-making. Traditional Naive Bayes classifiers,…
cs.LG2026
Novel Dynamic Batch-Sensitive Adam Optimiser for Vehicular Accident Injury Severity Prediction
Daniel Asare Kyei, Alimatu Saadia-Yussiff, Maame G. Asante-Mensah +3
The choice of optimiser is important in deep learning, as it strongly influences model efficiency and speed of convergence. However, many commonly used optimisers encounter difficu…
q-bio.BM2020
Deep Inverse Reinforcement Learning for Structural Evolution of Small Molecules
Brighter Agyemang, Wei-Ping Wu, Daniel Addo +3
The size and quality of chemical libraries to the drug discovery pipeline are crucial for developing new drugs or repurposing existing drugs. Existing techniques such as combinator…