Maya Gupta
25 papers · 2009–2022 · 6 venues · across top CS/AI venues
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Achievements
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(3)
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(13)
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(13)
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Century Club Β· Bronze
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(113)
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Top co-authors
Research topics
Machine Learning
(25)
Core Methods
(18)
Optimization & Theory
(15)
Application Areas
(11)
Artificial Intelligence
(8)
Mathematics & Optimization
(6)
Core AI
(6)
Learning Types
(6)
Optimization
(6)
Deep Learning
(2)
Architectures
(2)
Mathematics
(2)
Computer Science
(1)
Applications
(1)
Bayesian & Probabilistic
(1)
Keywords
constrained optimization
(6)
shape constraint
(4)
fairness constraint
(3)
look-up table
(3)
monotonicity constraint
(3)
lattice regression
(3)
monotonic function
(3)
deep lattice network
(2)
parameter estimation
(2)
neural network
(2)
ensemble learning
(2)
statistical parity
(2)
noisy label
(2)
function approximation
(2)
empirical risk minimization
(2)
algorithmic fairness
(2)
fairness metric
(2)
feature selection
(1)
black-box optimization
(1)
game theory
(1)
Papers
Global Optimization Networks
ICML 2022
Deep k-NN for Noisy Labels
ICML 2020
Deontological Ethics By Monotonicity Shape Constraints
AISTATS 2020
Multidimensional Shape Constraints
ICML 2020
Optimizing Black-box Metrics with Adaptive Surrogates
ICML 2020
Pairwise Fairness for Ranking and Regression
AAAI 2020
Robust Optimization for Fairness with Noisy Protected Groups
NeurIPS 2020
Metric-Optimized Example Weights
ICML 2019
On Making Stochastic Classifiers Deterministic
NeurIPS 2019
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals
JMLR 2019
Optimizing Generalized Rate Metrics with Three Players
NeurIPS 2019
Shape Constraints for Set Functions
ICML 2019
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
ICML 2019
Constrained Interacting Submodular Groupings
ICML 2018
Diminishing Returns Shape Constraints for Interpretability and Regularization
NeurIPS 2018
To Trust Or Not To Trust A Classifier
NeurIPS 2018
Deep Lattice Networks and Partial Monotonic Functions
NeurIPS 2017
A Light Touch for Heavily Constrained SGD
COLT 2016
Fast and Flexible Monotonic Functions with Ensembles of Lattices
NeurIPS 2016
Launch and Iterate: Reducing Prediction Churn
NeurIPS 2016
Monotonic Calibrated Interpolated Look-Up Tables
JMLR 2016
Satisfying Real-world Goals with Dataset Constraints
NeurIPS 2016
Multi-Task Averaging
NeurIPS 2012
Shadow Dirichlet for Restricted Probability Modeling
NeurIPS 2010
Lattice Regression
NeurIPS 2009