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Implicit Rate-Constrained Optimization of Non-decomposable Objectives


Jul 29, 2021
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter

* ICML 2021; Code available at https://github.com/google-research/google-research/tree/master/implicit_constrained_optimization 

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Training Over-parameterized Models with Non-decomposable Objectives


Jul 09, 2021
Harikrishna Narasimhan, Aditya Krishna Menon


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Churn Reduction via Distillation


Jun 04, 2021
Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh


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Optimizing Black-box Metrics with Iterative Example Weighting


Feb 18, 2021
Gaurush Hiranandani, Jatin Mathur, Oluwasanmi Koyejo, Mahdi Milani Fard, Harikrishna Narasimhan

* 41 pages, 3 figures, and 6 tables 

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Distilling Double Descent


Feb 13, 2021
Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou


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Quadratic Metric Elicitation with Application to Fairness


Nov 03, 2020
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo

* 32 pages, 9 figures, and 1 table 

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Fair Performance Metric Elicitation


Jun 23, 2020
Gaurush Hiranandani, Harikrishna Narasimhan, Oluwasanmi Koyejo

* 29 pages, 6 figures, and 2 tables 

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Robust Optimization for Fairness with Noisy Protected Groups


Feb 21, 2020
Serena Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya Gupta, Michael I. Jordan


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Optimizing Black-box Metrics with Adaptive Surrogates


Feb 20, 2020
Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya Gupta


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Optimizing Generalized Rate Metrics through Game Equilibrium


Sep 06, 2019
Harikrishna Narasimhan, Andrew Cotter, Maya Gupta


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Pairwise Fairness for Ranking and Regression


Jun 12, 2019
Harikrishna Narasimhan, Andrew Cotter, Maya Gupta, Serena Wang


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Optimal Auctions through Deep Learning


Mar 19, 2018
Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes


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Online Optimization Methods for the Quantification Problem


Jun 13, 2016
Purushottam Kar, Shuai Li, Harikrishna Narasimhan, Sanjay Chawla, Fabrizio Sebastiani

* 26 pages, 6 figures. A short version of this manuscript will appear in the proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2016 

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Support Vector Algorithms for Optimizing the Partial Area Under the ROC Curve


May 13, 2016
Harikrishna Narasimhan, Shivani Agarwal


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Surrogate Functions for Maximizing Precision at the Top


May 26, 2015
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain

* Journal of Machine Learning Research, W&CP 37 (2015) 
* To appear in the the proceedings of the 32nd International Conference on Machine Learning (ICML 2015) 

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Optimizing Non-decomposable Performance Measures: A Tale of Two Classes


May 26, 2015
Harikrishna Narasimhan, Purushottam Kar, Prateek Jain

* Journal of Machine Learning Research, W&CP 37 (2015) 
* To appear in proceedings of the 32nd International Conference on Machine Learning (ICML 2015) 

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Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics


Jan 01, 2015
Harish G. Ramaswamy, Harikrishna Narasimhan, Shivani Agarwal


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Online and Stochastic Gradient Methods for Non-decomposable Loss Functions


Oct 24, 2014
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain

* 25 pages, 3 figures, To appear in the proceedings of the 28th Annual Conference on Neural Information Processing Systems, NIPS 2014 

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