70 citations · 232 across the 36 of their papers we have counts for
5 papers · 1 filter
Learning Neural Activations
Fayyaz ul Amir Afsar Minhas, Amina Asif
An artificial neuron is modelled as a weighted summation followed by an activation function which determines its output. A wide variety of activation functions such as rectified li…
Generalized Learning with Rejection for Classification and Regression Problems
Amina Asif, Fayyaz ul Amir Afsar Minhas
Learning with rejection (LWR) allows development of machine learning systems with the ability to discard low confidence decisions generated by a prediction model. That is, just lik…
AMP0: Species-Specific Prediction of Anti-microbial Peptides using Zero and Few Shot Learning
Sadaf Gull, Fayyaz Minhas
The evolution of drug-resistant microbial species is one of the major challenges to global health. The development of new antimicrobial treatments such as antimicrobial peptides ne…
An embarrassingly simple approach to neural multiple instance classification
Amina Asif, Fayyaz ul Amir Afsar Minhas
Multiple Instance Learning (MIL) is a weak supervision learning paradigm that allows modeling of machine learning problems in which labels are available only for groups of examples…
Ten ways to fool the masses with machine learning
Fayyaz Minhas, Amina Asif, Asa Ben-Hur
If you want to tell people the truth, make them laugh, otherwise they'll kill you. (source unclear) Machine learning and deep learning are the technologies of the day for developin…