Publication date
May 2021
DOIAbstract
Code and datasets used to reproduce the experiments done in the paper "Fair Interpretable Representation Learning"
Code and datasets used to reproduce the experiments done in the paper "Fair Interpretable Representation Learning"
Raw data and analysis scripts associated with Experiment 1 in the paper "The Cost of Multiple Repres...
Abstract. Data of different levels of complexity and of ever growing diversity of characteristics ar...
We propose to learn invariant representations, in the data domain, to achieve interpretability in al...
Code and datasets used to reproduce the experiments done in the paper "Fair Interpretable Representa...
This dataset is used in the experiments in the paper "A First Look at Fairness of Automatic Code Rev...
Code and Experiments for "Fair Pairwise Learning to Rank", a paper published at the IEEE DSAA 2020 c...
This package contains the dataset and the replication source code used in the experiments in the pap...
Synbols: Probing Learning Algorithms with Synthetic Datasets Benchmark datasets generated using the...
The dataset reports participants judgments, the features of the judgment objects, and the correct cr...
codes of experiments and analysis which have been used for "Do Machine Learning Platforms Provide Ou...
This repository contains all code and data to reproduce the analyses and figures of the manuscript: ...
<p>Source code that can be used to reproduce the results of the experiments presented in the paper "...
The widespread use of machine learning models, especially within the context of decision-making syst...
Machine Learning has become more and more prominent in our daily lives as the Information Age and Fo...
Developing learning methods which do not discriminate subgroups in the population is the central goa...
Raw data and analysis scripts associated with Experiment 1 in the paper "The Cost of Multiple Repres...
Abstract. Data of different levels of complexity and of ever growing diversity of characteristics ar...
We propose to learn invariant representations, in the data domain, to achieve interpretability in al...
Code and datasets used to reproduce the experiments done in the paper "Fair Interpretable Representa...
This dataset is used in the experiments in the paper "A First Look at Fairness of Automatic Code Rev...
Code and Experiments for "Fair Pairwise Learning to Rank", a paper published at the IEEE DSAA 2020 c...
This package contains the dataset and the replication source code used in the experiments in the pap...
Synbols: Probing Learning Algorithms with Synthetic Datasets Benchmark datasets generated using the...
The dataset reports participants judgments, the features of the judgment objects, and the correct cr...
codes of experiments and analysis which have been used for "Do Machine Learning Platforms Provide Ou...
This repository contains all code and data to reproduce the analyses and figures of the manuscript: ...
<p>Source code that can be used to reproduce the results of the experiments presented in the paper "...
The widespread use of machine learning models, especially within the context of decision-making syst...
Machine Learning has become more and more prominent in our daily lives as the Information Age and Fo...
Developing learning methods which do not discriminate subgroups in the population is the central goa...
Raw data and analysis scripts associated with Experiment 1 in the paper "The Cost of Multiple Repres...
Abstract. Data of different levels of complexity and of ever growing diversity of characteristics ar...
We propose to learn invariant representations, in the data domain, to achieve interpretability in al...
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