Search Results for author: Ross Maciejewski

Found 4 papers, 2 papers with code

MultiFair: Multi-Group Fairness in Machine Learning

no code implementations24 May 2021 Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong

Algorithmic fairness is becoming increasingly important in data mining and machine learning, and one of the most fundamental notions is group fairness.


A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes

1 code implementation15 Sep 2020 Yuxin Ma, Arlen Fan, Jingrui He, Arun Reddy Nelakurthi, Ross Maciejewski

Transfer Learning is intended to relax this assumption by modeling relationships between domains, and is often applied in deep learning applications to reduce the demand for labeled data and training time.

Image Classification Transfer Learning

Diagnosing Concept Drift with Visual Analytics

no code implementations28 Jul 2020 Weikai Yang, Zhen Li, Mengchen Liu, Yafeng Lu, Kelei Cao, Ross Maciejewski, Shixia Liu

Concept drift is a phenomenon in which the distribution of a data stream changes over time in unforeseen ways, causing prediction models built on historical data to become inaccurate.

Text Classification

Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics

1 code implementation17 Jul 2019 Yuxin Ma, Tiankai Xie, Jundong Li, Ross Maciejewski

Machine learning models are currently being deployed in a variety of real-world applications where model predictions are used to make decisions about healthcare, bank loans, and numerous other critical tasks.

Data Poisoning

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