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05/24/2023
Personalized DP-SGD using Sampling Mechanisms
Personalized privacy becomes critical in deep learning for Trustworthy A...
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02/05/2023
Improving Fair Training under Correlation Shifts
Model fairness is an essential element for Trustworthy AI. While many te...
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09/22/2022
XClusters: Explainability-first Clustering
We study the problem of explainability-first clustering where explainabi...
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09/15/2022
iFlipper: Label Flipping for Individual Fairness
As machine learning becomes prevalent, mitigating any unfairness present...
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02/07/2022
Redactor: Targeted Disinformation Generation using Probabilistic Decision Boundaries
Information leakage is becoming a critical problem as various informatio...
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12/13/2021
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective
Software 2.0 is a fundamental shift in software engineering where machin...
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10/27/2021
Sample Selection for Fair and Robust Training
Fairness and robustness are critical elements of Trustworthy AI that nee...
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06/07/2021
MixRL: Data Mixing Augmentation for Regression using Reinforcement Learning
Data augmentation is becoming essential for improving regression accurac...
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01/15/2021
Responsible AI Challenges in End-to-end Machine Learning
Responsible AI is becoming critical as AI is widely used in our everyday...
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12/03/2020
FairBatch: Batch Selection for Model Fairness
Training a fair machine learning model is essential to prevent demograph...
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04/07/2020
Inspector Gadget: A Data Programming-based Labeling System for Industrial Images
As machine learning for images becomes democratized in the Software 2.0 ...
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03/10/2020
Slice Tuner: A Selective Data Collection Framework for Accurate and Fair Machine Learning Models
As machine learning becomes democratized in the era of Software 2.0, one...
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02/24/2020
FR-Train: A mutual information-based approach to fair and robust training
Trustworthy AI is a critical issue in machine learning where, in additio...
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04/22/2019
Data Cleaning for Accurate, Fair, and Robust Models: A Big Data - AI Integration Approach
The wide use of machine learning is fundamentally changing the software ...
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11/08/2018
A Survey on Data Collection for Machine Learning: a Big Data - AI Integration Perspective
Data collection is a major bottleneck in machine learning and an active ...
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07/16/2018
Automated Data Slicing for Model Validation:A Big data - AI Integration Approach
As machine learning systems become democratized, it becomes increasingly...
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07/16/2018
Slice Finder: Automated Data Slicing for Model Validation
As machine learning (ML) systems become democratized, it becomes increas...
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07/16/2018