Andrew Cotter

Publication Activity (10 Years)

Years Active: 2010-2022
Publications (10 Years): 29

Top Topics

Constrained Optimization

Robust Optimization

Top Venues

Publications

Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh
Churn Reduction via Distillation. ICLR (2022)
Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou
Distilling Double Descent. CoRR (2021)
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter
Implicit Rate-Constrained Optimization of Non-decomposable Objectives. CoRR (2021)
Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh
Churn Reduction via Distillation. CoRR (2021)
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter
Implicit rate-constrained optimization of non-decomposable objectives. ICML (2021)
Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Serena Wang
Pairwise Fairness for Ranking and Regression. AAAI (2020)
Serena Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan
Robust Optimization for Fairness with Noisy Protected Groups. CoRR (2020)
Serena Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan
Robust Optimization for Fairness with Noisy Protected Groups. NeurIPS (2020)
Harikrishna Narasimhan, Andrew Cotter, Yichen Zhou, Serena Wang, Wenshuo Guo
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models. NeurIPS (2020)
Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta
Optimizing Generalized Rate Metrics with Three Players. NeurIPS (2019)
Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Erez Louidor, James Muller, Taman Narayan, Serena Wang, Tao Zhu
Shape Constraints for Set Functions. ICML (2019)
Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta
Optimizing Generalized Rate Metrics through Game Equilibrium. CoRR (2019)
Andrew Cotter, Heinrich Jiang, Karthik Sridharan
Two-Player Games for Efficient Non-Convex Constrained Optimization. ALT (2019)
Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Serena Wang
Pairwise Fairness for Ranking and Regression. CoRR (2019)
Andrew Cotter, Heinrich Jiang, Maya R. Gupta, Serena 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 (2019)
Andrew Cotter, Maya R. Gupta, Harikrishna Narasimhan
On Making Stochastic Classifiers Deterministic. NeurIPS (2019)
Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Wang, Blake E. Woodworth, Seungil You
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. ICML (2019)
Andrew Cotter, Mahdi Milani Fard, Seungil You, Maya R. Gupta, Jeff A. Bilmes
Constrained Interacting Submodular Groupings. ICML (2018)
Maya R. Gupta, Dara Bahri, Andrew Cotter, Kevin Robert Canini
Diminishing Returns Shape Constraints for Interpretability and Regularization. NeurIPS (2018)
Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Wang, Blake E. Woodworth, Seungil You
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. CoRR (2018)
Maya R. Gupta, Andrew Cotter, Mahdi Milani Fard, Serena Wang
Proxy Fairness. CoRR (2018)
Andrew Cotter, Maya R. Gupta, Heinrich Jiang, James Muller, Taman Narayan, Serena Wang, Tao Zhu
Interpretable Set Functions. CoRR (2018)
Andrew Cotter, Heinrich Jiang, Serena 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 (2018)
Andrew Cotter, Heinrich Jiang, Karthik Sridharan
Two-Player Games for Efficient Non-Convex Constrained Optimization. CoRR (2018)
Andrew Cotter, Maya R. Gupta, Jan Pfeifer
A Light Touch for Heavily Constrained SGD. COLT (2016)
Andrew Cotter, Michael P. Friedlander, Gabriel Goh, Maya R. Gupta
Satisfying Real-world Goals with Dataset Constraints. CoRR (2016)
Gabriel Goh, Andrew Cotter, Maya R. Gupta, Michael P. Friedlander
Satisfying Real-world Goals with Dataset Constraints. NIPS (2016)
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 (2016)
Mahdi Milani Fard, Kevin Robert Canini, Andrew Cotter, Jan Pfeifer, Maya R. Gupta
Fast and Flexible Monotonic Functions with Ensembles of Lattices. NIPS (2016)
Maya R. Gupta, Andrew Cotter, Jan Pfeifer, Konstantin Voevodski, Kevin Robert Canini, Alexander Mangylov, Wojtek Moczydlowski
Monotonic Calibrated Interpolated Look-Up Tables. CoRR (2015)
Andrew Cotter, Maya R. Gupta, Jan Pfeifer
A Light Touch for Heavily Constrained SGD. CoRR (2015)
Andrew Cotter
Stochastic Optimization for Machine Learning. CoRR (2013)
Umut A. Acar, Andrew Cotter, Benoît Hudson, Duru Türkoglu
Dynamic well-spaced point sets. Comput. Geom. 46 (6) (2013)
Raman Arora, Andrew Cotter, Nathan Srebro
Stochastic Optimization of PCA with Capped MSG. CoRR (2013)
Andrew Cotter, Shai Shalev-Shwartz, Nati Srebro
Learning Optimally Sparse Support Vector Machines. ICML (1) (2013)
Raman Arora, Andrew Cotter, Nati Srebro
Stochastic Optimization of PCA with Capped MSG. NIPS (2013)
Andrew Cotter, Shai Shalev-Shwartz, Nathan Srebro
The Kernelized Stochastic Batch Perceptron. ICML (2012)
Andrew Cotter, Shai Shalev-Shwartz, Nathan Srebro
The Kernelized Stochastic Batch Perceptron CoRR (2012)
Raman Arora, Andrew Cotter, Karen Livescu, Nathan Srebro
Stochastic optimization for PCA and PLS. Allerton Conference (2012)
Andrew Cotter, Ohad Shamir, Nati Srebro, Karthik Sridharan
Better Mini-Batch Algorithms via Accelerated Gradient Methods. NIPS (2011)
Andrew Cotter, Nathan Srebro, Joseph Keshet
A GPU-tailored approach for training kernelized SVMs. KDD (2011)
Andrew Cotter, Ohad Shamir, Nathan Srebro, Karthik Sridharan
Better Mini-Batch Algorithms via Accelerated Gradient Methods CoRR (2011)
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro, Andrew Cotter
Pegasos: primal estimated sub-gradient solver for SVM. Math. Program. 127 (1) (2011)
Umut A. Acar, Andrew Cotter, Benoît Hudson, Duru Türkoglu
Parallelism in dynamic well-spaced point sets. SPAA (2011)
Andrew Cotter, Joseph Keshet, Nathan Srebro
Explicit Approximations of the Gaussian Kernel CoRR (2011)
Umut A. Acar, Andrew Cotter, Benoît Hudson, Duru Türkoglu
Dynamic well-spaced point sets. SCG (2010)