Gupta, Maya

24 publications

TMLR 2024 Expected Pinball Loss for Quantile Regression and Inverse CDF Estimation Taman Narayan, Serena Lutong Wang, Kevin Robert Canini, Maya Gupta

ICML 2022 Global Optimization Networks Sen Zhao, Erez Louidor, Maya Gupta

ICML 2020 Deep k-NN for Noisy Labels Dara Bahri, Heinrich Jiang, Maya Gupta

AISTATS 2020 Deontological Ethics by Monotonicity Shape Constraints Serena Wang, Maya Gupta

ICML 2020 Multidimensional Shape Constraints Maya Gupta, Erez Louidor, Oleksandr Mangylov, Nobu Morioka, Taman Narayan, Sen Zhao

ICML 2020 Optimizing Black-Box Metrics with Adaptive Surrogates Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya Gupta

NeurIPS 2020 Robust Optimization for Fairness with Noisy Protected Groups Serena Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya Gupta, Michael I. Jordan

ICML 2019 Metric-Optimized Example Weights Sen Zhao, Mahdi Milani Fard, Harikrishna Narasimhan, Maya Gupta

NeurIPS 2019 On Making Stochastic Classifiers Deterministic Andrew Cotter, Maya Gupta, Harikrishna Narasimhan

JMLR 2019 Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals Andrew Cotter, Heinrich Jiang, Maya Gupta, Serena Wang, Taman Narayan, Seungil You, Karthik Sridharan

NeurIPS 2019 Optimizing Generalized Rate Metrics with Three Players Harikrishna Narasimhan, Andrew Cotter, Maya Gupta

ICML 2019 Shape Constraints for Set Functions Andrew Cotter, Maya Gupta, Heinrich Jiang, Erez Louidor, James Muller, Tamann Narayan, Serena Wang, Tao Zhu

ICML 2019 Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints Andrew Cotter, Maya Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Wang, Blake Woodworth, Seungil You

ICML 2018 Constrained Interacting Submodular Groupings Andrew Cotter, Mahdi Milani Fard, Seungil You, Maya Gupta, Jeff Bilmes

NeurIPS 2018 Diminishing Returns Shape Constraints for Interpretability and Regularization Maya Gupta, Dara Bahri, Andrew Cotter, Kevin Canini

NeurIPS 2018 To Trust or Not to Trust a Classifier Heinrich Jiang, Been Kim, Melody Guan, Maya Gupta

NeurIPS 2017 Deep Lattice Networks and Partial Monotonic Functions Seungil You, David Ding, Kevin Canini, Jan Pfeifer, Maya Gupta

NeurIPS 2016 Fast and Flexible Monotonic Functions with Ensembles of Lattices Mahdi Milani Fard, Kevin Canini, Andrew Cotter, Jan Pfeifer, Maya Gupta

NeurIPS 2016 Launch and Iterate: Reducing Prediction Churn Mahdi Milani Fard, Quentin Cormier, Kevin Canini, Maya Gupta

JMLR 2016 Monotonic Calibrated Interpolated Look-up Tables Maya Gupta, Andrew Cotter, Jan Pfeifer, Konstantin Voevodski, Kevin Canini, Alexander Mangylov, Wojciech Moczydlowski, Alexander van Esbroeck

NeurIPS 2016 Satisfying Real-World Goals with Dataset Constraints Gabriel Goh, Andrew Cotter, Maya Gupta, Michael P Friedlander

NeurIPS 2012 Multi-Task Averaging Sergey Feldman, Maya Gupta, Bela Frigyik

NeurIPS 2010 Shadow Dirichlet for Restricted Probability Modeling Bela Frigyik, Maya Gupta, Yihua Chen

NeurIPS 2009 Lattice Regression Eric Garcia, Maya Gupta