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02/26/2023
Efficient fair PCA for fair representation learning
We revisit the problem of fair principal component analysis (PCA), where...
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12/23/2022
What You Like: Generating Explainable Topical Recommendations for Twitter Using Social Annotations
With over 500 million tweets posted per day, in Twitter, it is difficult...
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03/21/2022
Diverse Counterfactual Explanations for Anomaly Detection in Time Series
Data-driven methods that detect anomalies in times series data are ubiqu...
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12/23/2021
More Than Words: Towards Better Quality Interpretations of Text Classifiers
The large size and complex decision mechanisms of state-of-the-art text ...
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11/26/2021
Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models
With the increasing adoption of machine learning (ML) models and systems...
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09/07/2021
Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud
Understanding the predictions made by machine learning (ML) models and t...
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07/13/2021
DIVINE: Diverse Influential Training Points for Data Visualization and Model Refinement
As the complexity of machine learning (ML) models increases, resulting i...
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06/23/2021
Multi-objective Asynchronous Successive Halving
Hyperparameter optimization (HPO) is increasingly used to automatically ...
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06/08/2021
On the Lack of Robust Interpretability of Neural Text Classifiers
With the ever-increasing complexity of neural language models, practitio...
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05/10/2021
Loss-Aversively Fair Classification
The use of algorithmic (learning-based) decision making in scenarios tha...
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05/07/2021
Pairwise Fairness for Ordinal Regression
We initiate the study of fairness for ordinal regression, or ordinal cla...
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07/01/2020
Unifying Model Explainability and Robustness via Machine-Checkable Concepts
As deep neural networks (DNNs) get adopted in an ever-increasing number ...
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07/02/2018
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices
Discrimination via algorithmic decision making has received considerable...
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06/30/2017
From Parity to Preference-based Notions of Fairness in Classification
The adoption of automated, data-driven decision making in an ever expand...
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06/30/2017
On Fairness, Diversity and Randomness in Algorithmic Decision Making
Consider a binary decision making process where a single machine learnin...
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10/31/2016
The Case for Temporal Transparency: Detecting Policy Change Events in Black-Box Decision Making Systems
Bringing transparency to black-box decision making systems (DMS) has bee...
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10/26/2016
