Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals
Saloni Dash, Vineeth Balasubramanian, Amit Sharma
Winter Conference on Applications of Computer Vision (WACV) | January 2022
论文与出版物
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Domain Generalization using Causal Matching
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International Conference on Machine Learning (ICML) | July 2021
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Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
AAAI/ACM Conference on AI, Ethics, and Society (AIES) | April 2021
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The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Naman Goel, Alfonso Amayeulas, Amit Deshpande, Amit Sharma
AAAI Conference on Artificial Intelligence (AAAI) | February 2021
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DoWhy: An End-to-End Library for Causal Inference
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Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
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Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi
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Explaining Machine Learning Classifiers through Diverse Counterfactual Examples
Ramaravind K. Mothilal, Amit Sharma, Chenhao Tan
ACM Conference on Fairness, Accountability, and Transparency | January 2020
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Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
Divyat Mahajan, Chenhao Tan, Amit Sharma
CausalML: Machine Learning and Causal Inference for Improved Decision Making Workshop, NeurIPS 2019 | December 2019
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Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
-
-
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals
Saloni Dash, Vineeth Balasubramanian, Amit Sharma
Winter Conference on Applications of Computer Vision (WACV) | January 2022
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
AAAI/ACM Conference on AI, Ethics, and Society (AIES) | April 2021
-
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Naman Goel, Alfonso Amayeulas, Amit Deshpande, Amit Sharma
AAAI Conference on Artificial Intelligence (AAAI) | February 2021
-
DoWhy: An End-to-End Library for Causal Inference
November 2020
Causal Data Science Meeting (https://causalscience.org/)
-
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi
ICML 2020 | July 2020
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
Explaining Machine Learning Classifiers through Diverse Counterfactual Examples
Ramaravind K. Mothilal, Amit Sharma, Chenhao Tan
ACM Conference on Fairness, Accountability, and Transparency | January 2020
-
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
Divyat Mahajan, Chenhao Tan, Amit Sharma
CausalML: Machine Learning and Causal Inference for Improved Decision Making Workshop, NeurIPS 2019 | December 2019
-
-
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
-
-
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals
Saloni Dash, Vineeth Balasubramanian, Amit Sharma
Winter Conference on Applications of Computer Vision (WACV) | January 2022
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
AAAI/ACM Conference on AI, Ethics, and Society (AIES) | April 2021
-
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Naman Goel, Alfonso Amayeulas, Amit Deshpande, Amit Sharma
AAAI Conference on Artificial Intelligence (AAAI) | February 2021
-
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi
ICML 2020 | July 2020
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
Explaining Machine Learning Classifiers through Diverse Counterfactual Examples
Ramaravind K. Mothilal, Amit Sharma, Chenhao Tan
ACM Conference on Fairness, Accountability, and Transparency | January 2020
-
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
Divyat Mahajan, Chenhao Tan, Amit Sharma
CausalML: Machine Learning and Causal Inference for Improved Decision Making Workshop, NeurIPS 2019 | December 2019
-
-
-
DoWhy: An End-to-End Library for Causal Inference
November 2020
Causal Data Science Meeting (https://causalscience.org/)
-