Neural network-augmented locally adaptive linear regression model for tabular data
Creating an interpretable model with high predictive performance is crucial in eXplainable AI
(XAI) field. We introduce an interpretable neural network-based regression model for tabular …
(XAI) field. We introduce an interpretable neural network-based regression model for tabular …
[PDF][PDF] A user-centric approach to explainable AI in a security operation center environment.
HS Eriksson - 2022 - duo.uio.no
Living in the information age, countries, societies, and individuals become ever more
emerged in technology for each passing day. However, with every new software, hardware …
emerged in technology for each passing day. However, with every new software, hardware …
Towards XAI in the SOC–a user centric study of explainable alerts with SHAP and LIME
HS Eriksson, G Grov - … Conference on Big Data (Big Data), 2022 - ieeexplore.ieee.org
Many studies of the adoption of machine learning (ML) in Security Operation Centres
(SOCs) have pointed to a lack of transparency and explanation–and thus trust–as a barrier …
(SOCs) have pointed to a lack of transparency and explanation–and thus trust–as a barrier …
Reimagine Application Performance as a Graph: Novel Graph-Based Method for Performance Anomaly Classification in High-Performance Computing
Performance anomaly in High Performance Computing (HPC) can be defined as run-to-run
variation of an application in repeated runs with the same set of configuration parameters …
variation of an application in repeated runs with the same set of configuration parameters …
Novel Representation Learning Technique using Graphs for Performance Analytics
The performance analytics domain in High Performance Computing (HPC) uses tabular data
to solve regression problems, such as predicting the execution time. Existing Machine …
to solve regression problems, such as predicting the execution time. Existing Machine …