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Thu 12 Nov 2020 01:05 - 01:06 at Virtual room 1 - Fairness

Recent works in DNN testing show that DNN based image classifiers are susceptible to confusion and bias errors. A DNN model, even robust trained model can be highly confused between certain pair of objects or highly bias towards some object than others. In this paper, we propose a differentiable distance metric, which is highly correlated with confusion errors. We propose a repairing approach by increasing the distance between two classes during retraining the model to reduce the confusion errors. We evaluate our approaches on both single-label and multi-label classification models and datasets. Our results show that our approach effectively reduce confusion errors with very slight accuracy reduce.

Conference Day
Thu 12 Nov

Displayed time zone: (UTC) Coordinated Universal Time change

01:00 - 01:30
01:00
2m
Talk
Do the Machine Learning Models on a Crowd Sourced Platform Exhibit Bias? An Empirical Study on Model Fairness
Research Papers
Sumon BiswasIowa State University, USA, Hridesh RajanIowa State University, USA
Link to publication DOI Pre-print Media Attached
01:03
1m
Talk
Fairway: A Way to Build Fair ML Software
Research Papers
Joymallya ChakrabortyNorth Carolina State University, USA, Suvodeep MajumderNorth Carolina State University, USA, Zhe YuNorth Carolina State University, USA, Tim MenziesNorth Carolina State University, USA
DOI
01:05
1m
Talk
Repairing Confusion and Bias Errors for DNN-Based Image Classifiers
Student Research Competition
Yuchi TianColumbia University
DOI
01:07
1m
Talk
Towards Automated Verification of Smart Contract Fairness
Research Papers
Ye LiuNanyang Technological University, Singapore, Yi LiNanyang Technological University, Singapore, Shang-Wei LinNanyang Technological University, Singapore, Rong ZhaoNanyang Technological University, Singapore
DOI Pre-print
01:09
21m
Talk
Conversations on Fairness
Paper Presentations
Joymallya ChakrabortyNorth Carolina State University, USA, Sumon BiswasIowa State University, USA, Ye LiuNanyang Technological University, Singapore, Yi LiNanyang Technological University, Singapore, Yuchi TianColumbia University, M: Christian BirdMicrosoft Research