Amit Deshpande

Researcher

출판물

자료 보기:

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

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

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

Amit Deshpande

출판물

How Far Can Fairness Constraints Help Recover From Biased Data?

On comparing fair classifiers under data bias

Optimizing group-fair Plackett-Luce ranking models for relevance and ex-post fairness

Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes

On the Power of Randomization in Fair Classification and Representation

On the Problem of Underranking in Group-Fair Ranking

Learning and Generalization in Overparameterized Normalizing Flows

How Linguistically Fair are Multilingual Pre-Trained Language Models?

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Inframarginality Audit of Group-Fairness

Blood Count on a Smartphone Microscope: Challenges

Embedding Approximately Low-Dimensional l_2^2 Metrics into l_1

On Greedy Maximization of Entropy

How Far Can Fairness Constraints Help Recover From Biased Data?

Optimizing group-fair Plackett-Luce ranking models for relevance and ex-post fairness

On comparing fair classifiers under data bias

Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes

On the Power of Randomization in Fair Classification and Representation

On the Problem of Underranking in Group-Fair Ranking

Learning and Generalization in Overparameterized Normalizing Flows

How Linguistically Fair are Multilingual Pre-Trained Language Models?

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Inframarginality Audit of Group-Fairness

On Greedy Maximization of Entropy

Optimizing group-fair Plackett-Luce ranking models for relevance and ex-post fairness

On comparing fair classifiers under data bias

On the Power of Randomization in Fair Classification and Representation

Embedding Approximately Low-Dimensional l_2^2 Metrics into l_1

How Linguistically Fair are Multilingual Pre-Trained Language Models?

Blood Count on a Smartphone Microscope: Challenges

How Far Can Fairness Constraints Help Recover From Biased Data?

Optimizing group-fair Plackett-Luce ranking models for relevance and ex-post fairness

On comparing fair classifiers under data bias

Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes

On the Power of Randomization in Fair Classification and Representation

On the Problem of Underranking in Group-Fair Ranking

Learning and Generalization in Overparameterized Normalizing Flows

How Linguistically Fair are Multilingual Pre-Trained Language Models?

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Blood Count on a Smartphone Microscope: Challenges

Embedding Approximately Low-Dimensional l_2^2 Metrics into l_1

On Greedy Maximization of Entropy

Inframarginality Audit of Group-Fairness