3 citations · 5 across the 5 of their papers we have counts for
3 papers · 1 filter
An Exploratory Study of AI System Risk Assessment from the Lens of Data Distribution and Uncertainty
Zhijie Wang, Yuheng Huang, Lei Ma +3
Deep learning (DL) has become a driving force and has been widely adopted in many domains and applications with competitive performance. In practice, to solve the nontrivial and co…
Practical Insights of Repairing Model Problems on Image Classification
Akihito Yoshii, Susumu Tokumoto, Fuyuki Ishikawa
Additional training of a deep learning model can cause negative effects on the results, turning an initially positive sample into a negative one (degradation). Such degradation is…
NeuRecover: Regression-Controlled Repair of Deep Neural Networks with Training History
Shogo Tokui, Susumu Tokumoto, Akihito Yoshii +4
Systematic techniques to improve quality of deep neural networks (DNNs) are critical given the increasing demand for practical applications including safety-critical ones. The key…