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ORCIDAndrew Cotter
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- affiliation: Toyota Technological Institute at Chicago
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2020 – today
- 2022
[c23]Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh:
Churn Reduction via Distillation. ICLR 2022- 2021
- [c22]Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter:
Implicit rate-constrained optimization of non-decomposable objectives. ICML 2021: 5861-5871 - [i19]Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou:
Distilling Double Descent. CoRR abs/2102.06849 (2021) - [i18]Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh:
Churn Reduction via Distillation. CoRR abs/2106.02654 (2021) - [i17]Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter:
Implicit Rate-Constrained Optimization of Non-decomposable Objectives. CoRR abs/2107.10960 (2021) - 2020
- [c21]Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Serena Lutong Wang:
Pairwise Fairness for Ranking and Regression. AAAI 2020: 5248-5255 - [c20]Harikrishna Narasimhan, Andrew Cotter, Yichen Zhou, Serena Lutong Wang, Wenshuo Guo:
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models. NeurIPS 2020 - [c19]Serena Lutong Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan:
Robust Optimization for Fairness with Noisy Protected Groups. NeurIPS 2020 - [i16]Serena Lutong Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan:
Robust Optimization for Fairness with Noisy Protected Groups. CoRR abs/2002.09343 (2020)
2010 – 2019
- 2019
- [j4]Andrew Cotter, Heinrich Jiang, Maya R. Gupta, Serena Lutong Wang, Taman Narayan, Seungil You, Karthik Sridharan:
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals. J. Mach. Learn. Res. 20: 172:1-172:59 (2019) - [c18]Andrew Cotter, Heinrich Jiang, Karthik Sridharan:
Two-Player Games for Efficient Non-Convex Constrained Optimization. ALT 2019: 300-332 - [c17]Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Erez Louidor, James Muller, Taman Narayan, Serena Lutong Wang, Tao Zhu:
Shape Constraints for Set Functions. ICML 2019: 1388-1396 - [c16]Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You:
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. ICML 2019: 1397-1405 - [c15]Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta:
Optimizing Generalized Rate Metrics with Three Players. NeurIPS 2019: 10746-10757 - [c14]Andrew Cotter, Maya R. Gupta, Harikrishna Narasimhan:
On Making Stochastic Classifiers Deterministic. NeurIPS 2019: 10910-10920 - [i15]Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Serena Lutong Wang:
Pairwise Fairness for Ranking and Regression. CoRR abs/1906.05330 (2019) - [i14]Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta:
Optimizing Generalized Rate Metrics through Game Equilibrium. CoRR abs/1909.02939 (2019) - 2018
- [c13]Andrew Cotter, Mahdi Milani Fard, Seungil You, Maya R. Gupta, Jeff A. Bilmes:
Constrained Interacting Submodular Groupings. ICML 2018: 1076-1085 - [c12]Maya R. Gupta, Dara Bahri, Andrew Cotter, Kevin Robert Canini:
Diminishing Returns Shape Constraints for Interpretability and Regularization. NeurIPS 2018: 6835-6845 - [i13]Andrew Cotter, Heinrich Jiang, Karthik Sridharan:
Two-Player Games for Efficient Non-Convex Constrained Optimization. CoRR abs/1804.06500 (2018) - [i12]Andrew Cotter, Maya R. Gupta, Heinrich Jiang, James Muller, Taman Narayan, Serena Lutong Wang, Tao Zhu:
Interpretable Set Functions. CoRR abs/1806.00050 (2018) - [i11]Maya R. Gupta, Andrew Cotter, Mahdi Milani Fard, Serena Lutong Wang:
Proxy Fairness. CoRR abs/1806.11212 (2018) - [i10]Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You:
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. CoRR abs/1807.00028 (2018) - [i9]Andrew Cotter, Heinrich Jiang, Serena Lutong Wang, Taman Narayan, Maya R. Gupta, Seungil You, Karthik Sridharan:
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals. CoRR abs/1809.04198 (2018) - 2016
- [j3]Maya R. Gupta, Andrew Cotter, Jan Pfeifer, Konstantin Voevodski
, Kevin Robert Canini, Alexander Mangylov, Wojtek Moczydlowski, Alexander Van Esbroeck:
Monotonic Calibrated Interpolated Look-Up Tables. J. Mach. Learn. Res. 17: 109:1-109:47 (2016) - [c11]Andrew Cotter, Maya R. Gupta, Jan Pfeifer:
A Light Touch for Heavily Constrained SGD. COLT 2016: 729-771 - [c10]Gabriel Goh, Andrew Cotter, Maya R. Gupta, Michael P. Friedlander:
Satisfying Real-world Goals with Dataset Constraints. NIPS 2016: 2415-2423 - [c9]Mahdi Milani Fard, Kevin Robert Canini, Andrew Cotter, Jan Pfeifer, Maya R. Gupta:
Fast and Flexible Monotonic Functions with Ensembles of Lattices. NIPS 2016: 2919-2927 - [i8]Andrew Cotter, Michael P. Friedlander, Gabriel Goh, Maya R. Gupta:
Satisfying Real-world Goals with Dataset Constraints. CoRR abs/1606.07558 (2016) - 2015
- [i7]Maya R. Gupta, Andrew Cotter, Jan Pfeifer, Konstantin Voevodski, Kevin Robert Canini, Alexander Mangylov, Wojtek Moczydlowski:
Monotonic Calibrated Interpolated Look-Up Tables. CoRR abs/1505.06378 (2015) - [i6]Andrew Cotter, Maya R. Gupta, Jan Pfeifer:
A Light Touch for Heavily Constrained SGD. CoRR abs/1512.04960 (2015) - 2013
- [j2]Umut A. Acar, Andrew Cotter, Benoît Hudson, Duru Türkoglu:
Dynamic well-spaced point sets. Comput. Geom. 46(6): 756-773 (2013) - [c8]Andrew Cotter, Shai Shalev-Shwartz, Nati Srebro:
Learning Optimally Sparse Support Vector Machines. ICML (1) 2013: 266-274 - [c7]Raman Arora, Andrew Cotter, Nati Srebro:
Stochastic Optimization of PCA with Capped MSG. NIPS 2013: 1815-1823 - [i5]Raman Arora, Andrew Cotter, Nathan Srebro:
Stochastic Optimization of PCA with Capped MSG. CoRR abs/1307.1674 (2013) - [i4]Andrew Cotter:
Stochastic Optimization for Machine Learning. CoRR abs/1308.3509 (2013) - 2012
- [c6]Raman Arora, Andrew Cotter, Karen Livescu, Nathan Srebro:
Stochastic optimization for PCA and PLS. Allerton Conference 2012: 861-868 - [c5]Andrew Cotter, Shai Shalev-Shwartz, Nathan Srebro:
The Kernelized Stochastic Batch Perceptron. ICML 2012 - [i3]Andrew Cotter, Shai Shalev-Shwartz, Nathan Srebro:
The Kernelized Stochastic Batch Perceptron. CoRR abs/1204.0566 (2012) - 2011
- [j1]Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro, Andrew Cotter:
Pegasos: primal estimated sub-gradient solver for SVM. Math. Program. 127(1): 3-30 (2011) - [c4]Andrew Cotter, Nathan Srebro, Joseph Keshet:
A GPU-tailored approach for training kernelized SVMs. KDD 2011: 805-813 - [c3]Andrew Cotter, Ohad Shamir, Nati Srebro, Karthik Sridharan:
Better Mini-Batch Algorithms via Accelerated Gradient Methods. NIPS 2011: 1647-1655 - [c2]Umut A. Acar, Andrew Cotter, Benoît Hudson, Duru Türkoglu:
Parallelism in dynamic well-spaced point sets. SPAA 2011: 33-42 - [i2]Andrew Cotter, Ohad Shamir, Nathan Srebro, Karthik Sridharan:
Better Mini-Batch Algorithms via Accelerated Gradient Methods. CoRR abs/1106.4574 (2011) - [i1]Andrew Cotter, Joseph Keshet, Nathan Srebro:
Explicit Approximations of the Gaussian Kernel. CoRR abs/1109.4603 (2011) - 2010
- [c1]Umut A. Acar, Andrew Cotter, Benoît Hudson, Duru Türkoglu:
Dynamic well-spaced point sets. SCG 2010: 314-323
Coauthor Index
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