24 citations · 64 across the 30 of their papers we have counts for
5 papers · 2 filters
Random Walk-steered Majority Undersampling
Payel Sadhukhan, Arjun Pakrashi, Brian Mac Namee
In this work, we propose Random Walk-steered Majority Undersampling (RWMaU), which undersamples the majority points of a class imbalanced dataset, in order to balance the classes.…
Integrating Unsupervised Clustering and Label-specific Oversampling to Tackle Imbalanced Multi-label Data
Payel Sadhukhan, Arjun Pakrashi, Sarbani Palit +1
There is often a mixture of very frequent labels and very infrequent labels in multi-label datatsets. This variation in label frequency, a type class imbalance, creates a significa…
On the Importance of Regularisation & Auxiliary Information in OOD Detection
John Mitros, Brian Mac Namee
Neural networks are often utilised in critical domain applications (e.g. self-driving cars, financial markets, and aerospace engineering), even though they exhibit overconfident pr…
The Deep Radial Basis Function Data Descriptor (D-RBFDD) Network: A One-Class Neural Network for Anomaly Detection
Mehran H. Z. Bazargani, Arjun Pakrashi, Brian Mac Namee
Anomaly detection is a challenging problem in machine learning, and is even more so when dealing with instances that are captured in low-level, raw data representations without a w…
Predicting Illness for a Sustainable Dairy Agriculture: Predicting and Explaining the Onset of Mastitis in Dairy Cows
Cathal Ryan, Christophe Guéret, Donagh Berry +3
Mastitis is a billion dollar health problem for the modern dairy industry, with implications for antibiotic resistance. The use of AI techniques to identify the early onset of this…