1 citations · 1 across the 4 of their papers we have counts for
4 papers
Deep Feature Selection Using a Novel Complementary Feature Mask
Yiwen Liao, Jochen Rivoir, Raphaël Latty +1
Feature selection has drawn much attention over the last decades in machine learning because it can reduce data dimensionality while maintaining the original physical meaning of fe…
A Deep-Learning-Aided Pipeline for Efficient Post-Silicon Tuning
Yiwen Liao, Bin Yang, Raphaël Latty +1
In post-silicon validation, tuning is to find the values for the tuning knobs, potentially as a function of process parameters and/or known operating conditions. In this sense, an…
ORSA: Outlier Robust Stacked Aggregation for Best- and Worst-Case Approximations of Ensemble Systems\
Peter Domanski, Dirk Pflüger, Jochen Rivoir +1
In recent years, the usage of ensemble learning in applications has grown significantly due to increasing computational power allowing the training of large ensembles in reasonable…
Self-Learning Tuning for Post-Silicon Validation
Peter Domanski, Dirk Pflüger, Jochen Rivoir +1
Increasing complexity of modern chips makes design validation more difficult. Existing approaches are not able anymore to cope with the complexity of tasks such as robust performan…