How Far Can Fairness Constraints Help Recover From Biased Data?
Mohit Sharma, Amit Deshpande
ICML 2024 | July 2024
Amit Deshpande
Chercheur
Papiers de Collaboration
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On comparing fair classifiers under data bias
Mohit Sharma, Amit Deshpande, Avinash Anand
NeurIPS workshop Algorithmic Fairness through the Lens of Time | November 2023
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Optimizing group-fair Plackett-Luce ranking models for relevance and ex-post fairness
Sruthi Gorantla, Eshaan Bhansali, Amit Deshpande, Anand Louis
NeurIPS workshop OPT2023: Optimization for Machine Learning | November 2023
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Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes
Abhinav Kumar, Amit Deshpande, Amit Sharma
NeurIPS 2023 | October 2023
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On the Power of Randomization in Fair Classification and Representation
Sushant Agarwal, Amit Deshpande
ACM Conference on Fairness, Accountability, and Transparency (FAccT) | June 2022
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On the Problem of Underranking in Group-Fair Ranking
Sruthi Gorantla, Amit Deshpande, Anand Louis
2021 International Conference on Machine Learning | July 2021
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Learning and Generalization in Overparameterized Normalizing Flows
Kulin Shah, Amit Deshpande, Navin Goyal
AISTATS 2022 | June 2021
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How Linguistically Fair are Multilingual Pre-Trained Language Models?
Monojit Choudhury, Amit Deshpande
AAAI-21 | February 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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Inframarginality Audit of Group-Fairness
Amit Sharma, Arpita Biswas, Siddharth Barman
June 2020
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Blood Count on a Smartphone Microscope: Challenges
Uma P. Moravapalle, Amit Deshpande, Ashish Kapoor, Ramachandran Ramjee, Priya Ravi
HotMobile | February 2017
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Embedding Approximately Low-Dimensional l_2^2 Metrics into l_1
36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016) | December 2016
ISBN: 978-3-95977-027-9
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On Greedy Maximization of Entropy
Dravyansh Sharma, Ashish Kapoor, Amit Deshpande
Proceedings of The 32nd International Conference on Machine Learning | July 2015
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How Far Can Fairness Constraints Help Recover From Biased Data?
Mohit Sharma, Amit Deshpande
ICML 2024 | July 2024
-
Optimizing group-fair Plackett-Luce ranking models for relevance and ex-post fairness
Sruthi Gorantla, Eshaan Bhansali, Amit Deshpande, Anand Louis
NeurIPS workshop OPT2023: Optimization for Machine Learning | November 2023
-
On comparing fair classifiers under data bias
Mohit Sharma, Amit Deshpande, Avinash Anand
NeurIPS workshop Algorithmic Fairness through the Lens of Time | November 2023
-
Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes
Abhinav Kumar, Amit Deshpande, Amit Sharma
NeurIPS 2023 | October 2023
-
On the Power of Randomization in Fair Classification and Representation
Sushant Agarwal, Amit Deshpande
ACM Conference on Fairness, Accountability, and Transparency (FAccT) | June 2022
-
On the Problem of Underranking in Group-Fair Ranking
Sruthi Gorantla, Amit Deshpande, Anand Louis
2021 International Conference on Machine Learning | July 2021
-
Learning and Generalization in Overparameterized Normalizing Flows
Kulin Shah, Amit Deshpande, Navin Goyal
AISTATS 2022 | June 2021
-
How Linguistically Fair are Multilingual Pre-Trained Language Models?
Monojit Choudhury, Amit Deshpande
AAAI-21 | February 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
-
Inframarginality Audit of Group-Fairness
Amit Sharma, Arpita Biswas, Siddharth Barman
June 2020
-
On Greedy Maximization of Entropy
Dravyansh Sharma, Ashish Kapoor, Amit Deshpande
Proceedings of The 32nd International Conference on Machine Learning | July 2015
-
-
-
Optimizing group-fair Plackett-Luce ranking models for relevance and ex-post fairness
Sruthi Gorantla, Eshaan Bhansali, Amit Deshpande, Anand Louis
NeurIPS workshop OPT2023: Optimization for Machine Learning | November 2023
-
On comparing fair classifiers under data bias
Mohit Sharma, Amit Deshpande, Avinash Anand
NeurIPS workshop Algorithmic Fairness through the Lens of Time | November 2023
-
On the Power of Randomization in Fair Classification and Representation
Sushant Agarwal, Amit Deshpande
ACM Conference on Fairness, Accountability, and Transparency (FAccT) | June 2022
-
Embedding Approximately Low-Dimensional l_2^2 Metrics into l_1
36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016) | December 2016
ISBN: 978-3-95977-027-9
-
-
-
How Linguistically Fair are Multilingual Pre-Trained Language Models?
Monojit Choudhury, Amit Deshpande
AAAI-21 | February 2021
-
-
-
Blood Count on a Smartphone Microscope: Challenges
Uma P. Moravapalle, Amit Deshpande, Ashish Kapoor, Ramachandran Ramjee, Priya Ravi
HotMobile | February 2017
-
-
-
How Far Can Fairness Constraints Help Recover From Biased Data?
Mohit Sharma, Amit Deshpande
ICML 2024 | July 2024
-
Optimizing group-fair Plackett-Luce ranking models for relevance and ex-post fairness
Sruthi Gorantla, Eshaan Bhansali, Amit Deshpande, Anand Louis
NeurIPS workshop OPT2023: Optimization for Machine Learning | November 2023
-
On comparing fair classifiers under data bias
Mohit Sharma, Amit Deshpande, Avinash Anand
NeurIPS workshop Algorithmic Fairness through the Lens of Time | November 2023
-
Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes
Abhinav Kumar, Amit Deshpande, Amit Sharma
NeurIPS 2023 | October 2023
-
On the Power of Randomization in Fair Classification and Representation
Sushant Agarwal, Amit Deshpande
ACM Conference on Fairness, Accountability, and Transparency (FAccT) | June 2022
-
On the Problem of Underranking in Group-Fair Ranking
Sruthi Gorantla, Amit Deshpande, Anand Louis
2021 International Conference on Machine Learning | July 2021
-
Learning and Generalization in Overparameterized Normalizing Flows
Kulin Shah, Amit Deshpande, Navin Goyal
AISTATS 2022 | June 2021
-
How Linguistically Fair are Multilingual Pre-Trained Language Models?
Monojit Choudhury, Amit Deshpande
AAAI-21 | February 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
-
Blood Count on a Smartphone Microscope: Challenges
Uma P. Moravapalle, Amit Deshpande, Ashish Kapoor, Ramachandran Ramjee, Priya Ravi
HotMobile | February 2017
-
Embedding Approximately Low-Dimensional l_2^2 Metrics into l_1
36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016) | December 2016
ISBN: 978-3-95977-027-9
-
On Greedy Maximization of Entropy
Dravyansh Sharma, Ashish Kapoor, Amit Deshpande
Proceedings of The 32nd International Conference on Machine Learning | July 2015
-
-
-
Inframarginality Audit of Group-Fairness
Amit Sharma, Arpita Biswas, Siddharth Barman
June 2020
-