5 papers
Multiple Additive Neural Networks for Structured and Unstructured Data
Janis Mohr, Jörg Frochte
This paper extends and explains the Multiple Additive Neural Networks (MANN) methodology, an enhancement to the traditional Gradient Boosting framework, utilizing nearly shallow ne…
Responsible AI in Business
Stephan Sandfuchs, Diako Farooghi, Janis Mohr +3
Artificial intelligence (AI) and Machine Learning (ML) have moved from research and pilot projects into everyday business operations, with generative AI accelerating adoption acros…
One-Shot Identification with Different Neural Network Approaches
Janis Mohr, Jörg Frochte
Convolutional neural networks (CNNs) have been widely used in the computer vision community, significantly improving the state-of-the-art. But learning good features often is compu…
Exploring Student Expectations and Confidence in Learning Analytics
Hayk Asatryan, Basile Tousside, Janis Mohr +5
Learning Analytics (LA) is nowadays ubiquitous in many educational systems, providing the ability to collect and analyze student data in order to understand and optimize learning a…
Group and Exclusive Sparse Regularization-based Continual Learning of CNNs
Basile Tousside, Janis Mohr, Jörg Frochte
We present a regularization-based approach for continual learning (CL) of fixed capacity convolutional neural networks (CNN) that does not suffer from the problem of catastrophic f…