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07/20/2022
DataPerf: Benchmarks for Data-Centric AI Development
Machine learning (ML) research has generally focused on models, while th...
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11/10/2021
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics
Interpretability is becoming an active research topic as machine learnin...
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04/16/2021
Data Shapley Valuation for Efficient Batch Active Learning
Annotating the right set of data amongst all available data points is a ...
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10/15/2020
Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset
The reliability of machine learning models can be compromised when train...
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10/09/2020
How Does Mixup Help With Robustness and Generalization?
Mixup is a popular data augmentation technique based on taking convex co...
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06/15/2020
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Data augmentation by incorporating cheap unlabeled data from multiple do...
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02/27/2020
A Distributional Framework for Data Valuation
Shapley value is a classic notion from game theory, historically used to...
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02/23/2020
Neuron Shapley: Discovering the Responsible Neurons
We develop Neuron Shapley as a new framework to quantify the contributio...
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11/20/2019
DermGAN: Synthetic Generation of Clinical Skin Images with Pathology
Despite the recent success in applying supervised deep learning to medic...
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10/09/2019
Who's responsible? Jointly quantifying the contribution of the learning algorithm and training data
A fancy learning algorithm A outperforms a baseline method B when they a...
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04/05/2019
Data Shapley: Equitable Valuation of Data for Machine Learning
As data becomes the fuel driving technological and economic growth, a fu...
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02/07/2019
Automating Interpretability: Discovering and Testing Visual Concepts Learned by Neural Networks
Interpretability has become an important topic of research as more machi...
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07/17/2018
Knockoffs for the mass: new feature importance statistics with false discovery guarantees
An important problem in machine learning and statistics is to identify f...
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05/31/2018
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification
Machine learning predictors are successfully deployed in applications ra...
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10/29/2017