Andrew Cotter

According to our database, Andrew Cotter authored at least 33 papers between 2011 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

Churn Reduction via Distillation.

Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Distilling Double Descent.

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

CoRR, 2021

Implicit rate-constrained optimization of non-decomposable objectives.

Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Robust Optimization for Fairness with Noisy Protected Groups.

Serena Lutong Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Approximate Heavily-Constrained Learning with Lagrange Multiplier Models.

Harikrishna Narasimhan, Andrew Cotter, Yichen Zhou, Serena Lutong Wang, Wenshuo Guo

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Pairwise Fairness for Ranking and Regression.

Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Serena Lutong Wang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals.

Andrew Cotter, Heinrich Jiang, Maya R. Gupta, Serena Lutong Wang, Taman Narayan, Seungil You, Karthik Sridharan

J. Mach. Learn. Res., 2019

Optimizing Generalized Rate Metrics through Game Equilibrium.

Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta

CoRR, 2019

Optimizing Generalized Rate Metrics with Three Players.

Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On Making Stochastic Classifiers Deterministic.

Andrew Cotter, Maya R. Gupta, Harikrishna Narasimhan

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints.

Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You

Proceedings of the 36th International Conference on Machine Learning, 2019

Shape Constraints for Set Functions.

Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Erez Louidor, James Muller, Taman Narayan, Serena Lutong Wang, Tao Zhu

Proceedings of the 36th International Conference on Machine Learning, 2019

Two-Player Games for Efficient Non-Convex Constrained Optimization.

Andrew Cotter, Heinrich Jiang, Karthik Sridharan

Proceedings of the Algorithmic Learning Theory, 2019

2018

Proxy Fairness.

Maya R. Gupta, Andrew Cotter, Mahdi Milani Fard, Serena Lutong Wang

CoRR, 2018

Interpretable Set Functions.

Andrew Cotter, Maya R. Gupta, Heinrich Jiang, James Muller, Taman Narayan, Serena Lutong Wang, Tao Zhu

CoRR, 2018

Diminishing Returns Shape Constraints for Interpretability and Regularization.

Maya R. Gupta, Dara Bahri, Andrew Cotter, Kevin Robert Canini

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Constrained Interacting Submodular Groupings.

Andrew Cotter, Mahdi Milani Fard, Seungil You, Maya R. Gupta, Jeff A. Bilmes

Proceedings of the 35th International Conference on Machine Learning, 2018

2016

Monotonic Calibrated Interpolated Look-Up Tables.

Maya R. Gupta, Andrew Cotter, Jan Pfeifer, Konstantin Voevodski, Kevin Robert Canini, Alexander Mangylov, Wojtek Moczydlowski, Alexander Van Esbroeck

J. Mach. Learn. Res., 2016

Satisfying Real-world Goals with Dataset Constraints.

Gabriel Goh, Andrew Cotter, Maya R. Gupta, Michael P. Friedlander

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Fast and Flexible Monotonic Functions with Ensembles of Lattices.

Mahdi Milani Fard, Kevin Robert Canini, Andrew Cotter, Jan Pfeifer, Maya R. Gupta

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Light Touch for Heavily Constrained SGD.

Andrew Cotter, Maya R. Gupta, Jan Pfeifer

Proceedings of the 29th Conference on Learning Theory, 2016

2015

Monotonic Calibrated Interpolated Look-Up Tables.

Maya R. Gupta, Andrew Cotter, Jan Pfeifer, Konstantin Voevodski, Kevin Robert Canini, Alexander Mangylov, Wojtek Moczydlowski

CoRR, 2015

2013

Stochastic Optimization for Machine Learning.

Andrew Cotter

CoRR, 2013

Dynamic well-spaced point sets.

Umut A. Acar, Andrew Cotter, Benoît Hudson, Duru Türkoglu

Comput. Geom., 2013

Stochastic Optimization of PCA with Capped MSG.

Raman Arora, Andrew Cotter, Nati Srebro

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Learning Optimally Sparse Support Vector Machines.

Andrew Cotter, Shai Shalev-Shwartz, Nati Srebro

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

The Kernelized Stochastic Batch Perceptron.

Andrew Cotter, Shai Shalev-Shwartz, Nathan Srebro

Proceedings of the 29th International Conference on Machine Learning, 2012

Stochastic optimization for PCA and PLS.

Raman Arora, Andrew Cotter, Karen Livescu, Nathan Srebro

Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2011

Pegasos: primal estimated sub-gradient solver for SVM.

Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro, Andrew Cotter

Math. Program., 2011

Explicit Approximations of the Gaussian Kernel

Andrew Cotter, Joseph Keshet, Nathan Srebro

CoRR, 2011

Parallelism in dynamic well-spaced point sets.

Umut A. Acar, Andrew Cotter, Benoît Hudson, Duru Türkoglu

Proceedings of the SPAA 2011: Proceedings of the 23rd Annual ACM Symposium on Parallelism in Algorithms and Architectures, 2011

Better Mini-Batch Algorithms via Accelerated Gradient Methods.

Andrew Cotter, Ohad Shamir, Nati Srebro, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A GPU-tailored approach for training kernelized SVMs.

Andrew Cotter, Nathan Srebro, Joseph Keshet

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011