Maya R. Gupta

According to our database1, Maya R. Gupta authored at least 111 papers between 2000 and 2024.

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Bibliography

2024
Expected Pinball Loss For Quantile Regression And Inverse CDF Estimation.
Trans. Mach. Learn. Res., 2024

2022
Global Optimization Networks.
CoRR, 2022

Global Optimization Networks.
Proceedings of the International Conference on Machine Learning, 2022

2021
Fast Linear Interpolation.
ACM J. Emerg. Technol. Comput. Syst., 2021

Quit When You Can: Efficient Evaluation of Ensembles by Optimized Ordering.
ACM J. Emerg. Technol. Comput. Syst., 2021

Regularization Strategies for Quantile Regression.
CoRR, 2021

Bootstrapping for Batch Active Sampling.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020
Robust Optimization for Fairness with Noisy Protected Groups.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimizing Black-box Metrics with Adaptive Surrogates.
Proceedings of the 37th International Conference on Machine Learning, 2020

Multidimensional Shape Constraints.
Proceedings of the 37th International Conference on Machine Learning, 2020

Deep k-NN for Noisy Labels.
Proceedings of the 37th International Conference on Machine Learning, 2020

Deontological Ethics By Monotonicity Shape Constraints.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Pairwise Fairness for Ranking and Regression.
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.
J. Mach. Learn. Res., 2019

Optimizing Generalized Rate Metrics through Game Equilibrium.
CoRR, 2019

Minimum-Margin Active Learning.
CoRR, 2019

Optimizing Generalized Rate Metrics with Three Players.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On Making Stochastic Classifiers Deterministic.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Metric-Optimized Example Weights.
Proceedings of the 36th International Conference on Machine Learning, 2019

Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints.
Proceedings of the 36th International Conference on Machine Learning, 2019

Shape Constraints for Set Functions.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Proxy Fairness.
CoRR, 2018

Quit When You Can: Efficient Evaluation of Ensembles with Ordering Optimization.
CoRR, 2018

Interpretable Set Functions.
CoRR, 2018

To Trust Or Not To Trust A Classifier.
CoRR, 2018

Metric-Optimized Example Weights.
CoRR, 2018

To Trust Or Not To Trust A Classifier.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Diminishing Returns Shape Constraints for Interpretability and Regularization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Constrained Interacting Submodular Groupings.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Deep Lattice Networks and Partial Monotonic Functions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Monotonic Calibrated Interpolated Look-Up Tables.
J. Mach. Learn. Res., 2016

Satisfying Real-world Goals with Dataset Constraints.
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.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Launch and Iterate: Reducing Prediction Churn.
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.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Monotonic Calibrated Interpolated Look-Up Tables.
CoRR, 2015

2014
Training highly multiclass classifiers.
J. Mach. Learn. Res., 2014

Revisiting Stein's paradox: multi-task averaging.
J. Mach. Learn. Res., 2014

2013
Classifying with confidence from incomplete information.
J. Mach. Learn. Res., 2013

Similarity-based clustering by left-stochastic matrix factorization.
J. Mach. Learn. Res., 2013

Contact clustering and fusion for preprocessing multistatic active sonar data.
Proceedings of the 16th International Conference on Information Fusion, 2013

2012
Bounds on the Bayes Error Given Moments.
IEEE Trans. Inf. Theory, 2012

Optimized Regression for Efficient Function Evaluation.
IEEE Trans. Image Process., 2012

Multi-Task Averaging.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Dimensionality Reduction by Local Discriminative Gaussians.
Proceedings of the 29th International Conference on Machine Learning, 2012

Reliable early classification of time series.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Subjective evaluations of example-based, total variation, and joint regularization for image processing.
Proceedings of the Computational Imaging X, 2012

2011
Channel-Robust Classifiers.
IEEE Trans. Signal Process., 2011

Bounds on the Maximum Bayes Error Given Moments
CoRR, 2011

Multi-task Regularization of Generative Similarity Models.
Proceedings of the Similarity-Based Pattern Recognition - First International Workshop, 2011

Clustering by Left-Stochastic Matrix Factorization.
Proceedings of the 28th International Conference on Machine Learning, 2011

Clutter rejection by clustering likelihood-based similarities.
Proceedings of the 14th International Conference on Information Fusion, 2011

Minimizing bearing bias in tracking by de-coupled rotation and translation estimates.
Proceedings of the 14th International Conference on Information Fusion, 2011

2010
Completely Lazy Learning.
IEEE Trans. Knowl. Data Eng., 2010

Theory and Use of the EM Algorithm.
Found. Trends Signal Process., 2010

Parametric Bayesian Estimation of Differential Entropy and Relative Entropy.
Entropy, 2010

Shadow Dirichlet for Restricted Probability Modeling.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Optimized Construction of ICC Profiles by Lattice Regression.
Proceedings of the 18th Color and Imaging Conference, 2010

Training a support vector machine to classify signals in a real environment given clean training data.
Proceedings of the IEEE International Conference on Acoustics, 2010

Robust sequential classification of tracks.
Proceedings of the 13th Conference on Information Fusion, 2010

Estimation of position from multistatic Doppler measurements.
Proceedings of the 13th Conference on Information Fusion, 2010

Bayesian and pairwise local similarity discriminant analysis.
Proceedings of the 2nd International Workshop on Cognitive Information Processing, 2010

2009
A Quasi EM Method for Estimating Multiple Transmitter Locations.
IEEE Signal Process. Lett., 2009

Similarity-based Classification: Concepts and Algorithms.
J. Mach. Learn. Res., 2009

Lattice Regression.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Building Accurate and Smooth ICC Profiles by Lattice Regression.
Proceedings of the 17th Color and Imaging Conference, 2009

Regularizing the Local Similarity Discriminant Analysis Classifier.
Proceedings of the International Conference on Machine Learning and Applications, 2009

Learning kernels from indefinite similarities.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Estimating multiple transmitter locations from power measurements at multiple receivers.
Proceedings of the IEEE International Conference on Acoustics, 2009

Filtering web text to match target genres.
Proceedings of the IEEE International Conference on Acoustics, 2009

Part-of-speech histograms for genre classification of text.
Proceedings of the IEEE International Conference on Acoustics, 2009

Sequential Bayesian estimation of the probability of detection for tracking.
Proceedings of the 12th International Conference on Information Fusion, 2009

Fusing similarities and kernels for classification.
Proceedings of the 12th International Conference on Information Fusion, 2009

Fusing similarities and Euclidean features with generative classifiers.
Proceedings of the 12th International Conference on Information Fusion, 2009

Joint deconvolution and imaging.
Proceedings of the Computational Imaging VII, 2009

Gradient estimation in global optimization algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009

2008
Functional Bregman Divergence and Bayesian Estimation of Distributions.
IEEE Trans. Inf. Theory, 2008

Adaptive Local Linear Regression With Application to Printer Color Management.
IEEE Trans. Image Process., 2008

Generative models for similarity-based classification.
Pattern Recognit., 2008

Learning custom color transformations with adaptive neighborhoods.
J. Electronic Imaging, 2008

Bayesian estimation of the entropy of the multivariate Gaussian.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008

Functional Bregman divergence.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008

Cost-sensitive multi-class classification from probability estimates.
Proceedings of the Machine Learning, 2008

Multiresolutional regularization of local linear regression over adaptive neighborhoods for color management.
Proceedings of the International Conference on Image Processing, 2008

2007
Linear Fusion of Image Sets for Display.
IEEE Trans. Geosci. Remote. Sens., 2007

OCR binarization and image pre-processing for searching historical documents.
Pattern Recognit., 2007

Bayesian Quadratic Discriminant Analysis.
J. Mach. Learn. Res., 2007

Maximum Entropy Generative Models for Similarity-based Learning.
Proceedings of the IEEE International Symposium on Information Theory, 2007

Local similarity discriminant analysis.
Proceedings of the Machine Learning, 2007

SNR-Adaptive Linear Fusion of Hyperspectral Images for Color Display.
Proceedings of the International Conference on Image Processing, 2007

Color Management of Printers by Regression over Enclosing Neighborhoods.
Proceedings of the International Conference on Image Processing, 2007

Beamforming Alternatives for Multi-Channel Transient Acoustic Event Classification.
Proceedings of the IEEE International Conference on Acoustics, 2007

Joint Deconvolution and Classification for Signals with Multipath.
Proceedings of the IEEE International Conference on Acoustics, 2007

Ranked dither for robust color printing.
Proceedings of the Color Imaging XII: Processing, Hardcopy, and Applications, San Jose, 2007

An EM Technique for Multiple Transmitter Localization.
Proceedings of the 41st Annual Conference on Information Sciences and Systems, 2007

2006
Nonparametric Supervised Learning by Linear Interpolation with Maximum Entropy.
IEEE Trans. Pattern Anal. Mach. Intell., 2006

Distribution-based Bayesian Minimum Expected Risk for Discriminant Analysis.
Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006

Information-theoretic and Set-theoretic Similarity.
Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006

Wavelet Principal Component Analysis and its Application to Hyperspectral Images.
Proceedings of the International Conference on Image Processing, 2006

A Multiresolutional Estimated Gradient Architecture for Global Optimization.
Proceedings of the IEEE International Conference on Evolutionary Computation, 2006

2005
Design goals and solutions for display of hyperspectral images.
IEEE Trans. Geosci. Remote. Sens., 2005

Custom color enhancements by statistical learning.
Proceedings of the 2005 International Conference on Image Processing, 2005

Segmenting for Wavelet Compression.
Proceedings of the 2005 Data Compression Conference (DCC 2005), 2005

Simulating the effect of illumination using color transformations.
Proceedings of the Computational Imaging III, San Jose, 2005

2004
A principle of minimum expected risk.
Proceedings of the 2004 IEEE International Symposium on Information Theory, 2004

Inverting color transforms.
Proceedings of the Computational Imaging II, San Jose, 2004

2003
Analysis and classification of internal pipeline images.
Proceedings of the 2003 International Conference on Image Processing, 2003

Halftoning on the wavelet domain.
Proceedings of the Color Imaging VIII: Processing, Hardcopy, and Applications, Santa Clara, 2003

2002
Two-stage color palettization for error diffusion.
Proceedings of the Human Vision and Electronic Imaging VII, 2002

2001
Color conversions using maximum entropy estimation.
Proceedings of the 2001 International Conference on Image Processing, 2001

2000
Block Color Quantization: A New Method for Color Halftoning.
Proceedings of the 2000 International Conference on Image Processing, 2000


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