1 citations · 1 across the 4 of their papers we have counts for
4 papers
Phantom Embeddings: Using Embedding Space for Model Regularization in Deep Neural Networks
Mofassir ul Islam Arif, Mohsan Jameel, Josif Grabocka +1
The strength of machine learning models stems from their ability to learn complex function approximations from data; however, this strength also makes training deep neural networks…
Directly Optimizing IoU for Bounding Box Localization
Mofassir ul Islam Arif, Mohsan Jameel, Lars Schmidt-Thieme
Object detection has seen remarkable progress in recent years with the introduction of Convolutional Neural Networks (CNN). Object detection is a multi-task learning problem where…
A.I. and Data-Driven Mobility at Volkswagen Financial Services AG
Shayan Jawed, Mofassir ul Islam Arif, Ahmed Rashed +8
Machine learning is being widely adapted in industrial applications owing to the capabilities of commercially available hardware and rapidly advancing research. Volkswagen Financia…
Disturbing Target Values for Neural Network Regularization
Yongho Kim, Hanna Lukashonak, Paweena Tarepakdee +2
Diverse regularization techniques have been developed such as L2 regularization, Dropout, DisturbLabel (DL) to prevent overfitting. DL, a newcomer on the scene, regularizes the los…