1 citations · 1 across the 3 of their papers we have counts for
7 papers
Experts in the Loop: Conditional Variable Selection for Accelerating Post-Silicon Analysis Based on Deep Learning
Yiwen Liao, Raphaël Latty, Bin Yang
Post-silicon validation is one of the most critical processes in modern semiconductor manufacturing. Specifically, correct and deep understanding in test cases of manufactured devi…
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…
Anomaly Detection Based on Selection and Weighting in Latent Space
Yiwen Liao, Alexander Bartler, Bin Yang
With the high requirements of automation in the era of Industry 4.0, anomaly detection plays an increasingly important role in higher safety and reliability in the production and m…
Feature Selection Using Batch-Wise Attenuation and Feature Mask Normalization
Yiwen Liao, Raphaël Latty, Bin Yang
Feature selection is generally used as one of the most important preprocessing techniques in machine learning, as it helps to reduce the dimensionality of data and assists research…
Open-Set Recognition Using Intra-Class Splitting
Patrick Schlachter, Yiwen Liao, Bin Yang
This paper proposes a method to use deep neural networks as end-to-end open-set classifiers. It is based on intra-class data splitting. In open-set recognition, only samples from a…
Deep One-Class Classification Using Intra-Class Splitting
Patrick Schlachter, Yiwen Liao, Bin Yang
This paper introduces a generic method which enables to use conventional deep neural networks as end-to-end one-class classifiers. The method is based on splitting given data from…