Maya Gupta
 Research Area(s)
 Algorithms and Theory
 Machine Intelligence
 Machine Perception
CoAuthors
Gupta joined Google Research in 2012. Before Google, Gupta was an Associate Professor of Electrical Engineering at the University of Washington (20032012), tenured in 2009. Her research group focused on statistical learning algorithms for signal processing and color image processing. In 2007, Gupta received the PECASE award from Pres. George Bush for her work in classifying uncertain (e.g. random) signals, and received the 2007 Office of Naval Research YIP Award. Gupta graduated 9 Ph.D. students and 7 M.S students. Her Ph.D. in Electrical Engineering is from Stanford University (2003), where she was a National Science Foundation Graduate Fellow and worked with Bob Gray, Rob Tibshirani, and Richard Olshen. Before 2003, Gupta worked for Ricoh Research, NATO's Undersea Research Center, HP R&D, AT&T Labs, and Microsoft. Gupta also runs Artifact Puzzles, the second largest US maker of wooden jigsaw puzzles, a company she founded in 2009.
Google Publications

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

A Light Touch for Heavily Constrained SGD
Andrew Cotter, Maya Gupta, Jan Pfeifer
COLT (2016)

Fast and Flexible Monotonic Functions with Ensembles of Lattices
Kevin Canini, Andy Cotter, Mahdi Milani Fard, Maya Gupta, Jan Pfeifer
NIPS (2016)

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

Monotonic Calibrated Interpolated LookUp Tables
Maya Gupta, Andrew Cotter, Jan Pfeifer, Konstantin Voevodski, Kevin Canini, Alexander Mangylov, Wojciech Moczydlowski, Alexander van Esbroeck
Journal Machine Learning Research (JMLR) (2016)

Satisfying Realworld Goals with Dataset Constraints
Gabriel Goh, Andy Cotter, Maya Gupta, Michael Friedlander
NIPS (2016)

Revisiting Stein's Paradox: MultiTask Averaging
Sergey Feldman, Maya R. Gupta, Bela A. Frigyik
Journal Machine Learning Research, vol. 15 (2014)

Training Highly Multiclass Linear Classifiers
Maya R. Gupta, Samy Bengio, Jason Weston
Journal Machine Learning Research (JMLR) (2014), 1461−1492

Classifying with Confidence From Incomplete Test Data
Nathan Parris, Hyrum S. Anderson, Maya R. Gupta, Dun Yu Hsaio
Journal Machine Learning Research (JMLR), vol. 14 (2013)

Similaritybased Clustering by LeftStochastic Matrix Factorization
Raman Arora, Maya R. Gupta, Amol Kapila, Maryam Fazel
Journal Machine Learning Research (JMLR), vol. 14 (2013), pp. 17151746
Previous Publications

Bounds on the Bayes Error Given Moments
Bela Frigyik, Maya R. Gupta
IEEE Trans. Information Theory, vol. 58 (2012), pp. 36063612

Dimensionality Reduction by Local Discriminative Gaussians
Nathan Parrish, Maya R. Gupta
ICML (2012)

MultiTask Averaging
Sergey Feldman, Maya R. Gupta, Bela A. Frigyik
NIPS (2012), pp. 11781186

Optimized Regression for Efficient Function Evaluation
Eric K. Garcia, Raman Arora, Maya R. Gupta
IEEE Transactions on Image Processing, vol. 21 (2012), pp. 41284140

Reliable early classification of time series
Hyrum S. Anderson, Nathan Parrish, Kristi Tsukida, Maya R. Gupta
ICASSP (2012), pp. 20732076

ChannelRobust Classifiers
Hyrum S. Anderson, Maya R. Gupta, Eric Swanson, Kevin G. Jamieson
IEEE Transactions on Signal Processing, vol. 59 (2011), pp. 14211434

Clustering by LeftStochastic Matrix Factorization
Raman Arora, Maya R. Gupta, Amol Kapila, Maryam Fazel
ICML (2011), pp. 761768

Clutter rejection by clustering likelihoodbased similarities
Evan Hanusa, David W. Krout, Maya R. Gupta
FUSION (2011), pp. 16

Minimizing bearing bias in tracking by decoupled rotation and translation estimates
Raman Arora, Maya R. Gupta
FUSION (2011), pp. 17

Completely Lazy Learning
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, Santosh Srivastava
IEEE Trans. Knowl. Data Eng., vol. 22 (2010), pp. 12741285

Estimation of position from multistatic Doppler measurements
Evan Hanusa, David W. Krout, Maya R. Gupta
FUSION (2010), pp. 17

Parametric Bayesian Estimation of Differential Entropy and Relative Entropy
Maya R. Gupta, Santosh Srivastava
Entropy, vol. 12 (2010), pp. 818843

Robust sequential classification of tracks
Nathan Parrish, Hyrum S. Anderson, Maya R. Gupta
FUSION (2010), pp. 18

Shadow Dirichlet for Restricted Probability Modeling
Bela A. Frigyik, Maya R. Gupta, Yihua Chen
NIPS (2010), pp. 613621

Theory and Use of the EM Algorithm
Maya R. Gupta, Yihua Chen
Foundations and Trends in Signal Processing, vol. 4 (2010), pp. 223296

Training a support vector machine to classify signals in a real environment given clean training data
Kevin G. Jamieson, Maya R. Gupta, Eric Swanson, Hyrum S. Anderson
ICASSP (2010), pp. 22142217

A Quasi EM Method for Estimating Multiple Transmitter Locations
Jill K. Nelson, Maya R. Gupta, Jaime E. Almodovar, William H. Mortensen
IEEE Signal Process. Lett., vol. 16 (2009), pp. 354357

Estimating multiple transmitter locations from power measurements at multiple receivers
Jill K. Nelson, Jaime E. Almodovar, Maya R. Gupta, William H. Mortensen
ICASSP (2009), pp. 27612764

Filtering web text to match target genres
Marius A. Marin, Sergey Feldman, Mari Ostendorf, Maya R. Gupta
ICASSP (2009), pp. 37053708

Fusing similarities and Euclidean features with generative classifiers
Luca Cazzanti, Maya R. Gupta, Santosh Srivastava
FUSION (2009), pp. 224231

Fusing similarities and kernels for classification
Yihua Chen, Maya R. Gupta
FUSION (2009), pp. 474481

Gradient estimation in global optimization algorithms
Megan Hazen, Maya R. Gupta
IEEE Congress on Evolutionary Computation (2009), pp. 18411848

Joint deconvolution and imaging
Hyrum S. Anderson, Maya R. Gupta
Computational Imaging (2009), pp. 72460

Lattice Regression
Eric K. Garcia, Maya R. Gupta
NIPS (2009), pp. 594602

Learning kernels from indefinite similarities
Yihua Chen, Maya R. Gupta, Benjamin Recht
ICML (2009), pp. 19

Partofspeech histograms for genre classification of text
Sergey Feldman, Marius A. Marin, Mari Ostendorf, Maya R. Gupta
ICASSP (2009), pp. 47814784

Regularizing the Local Similarity Discriminant Analysis Classifier
Luca Cazzanti, Maya R. Gupta
ICMLA (2009), pp. 184189

Sequential Bayesian estimation of the probability of detection for tracking
Kevin G. Jamieson, Maya R. Gupta, David W. Krout
FUSION (2009), pp. 641648

Similaritybased Classification: Concepts and Algorithms
Yihua Chen, Eric K. Garcia, Maya R. Gupta, Ali Rahimi, Luca Cazzanti
Journal of Machine Learning Research, vol. 10 (2009), pp. 747776

Adaptive Local Linear Regression With Application to Printer Color Management
Maya R. Gupta, Eric K. Garcia, E. Chin
IEEE Transactions on Image Processing, vol. 17 (2008), pp. 936945

Bayesian estimation of the entropy of the multivariate Gaussian
Santosh Srivastava, Maya R. Gupta
ISIT (2008), pp. 11031107

Costsensitive multiclass classification from probability estimates
Deirdre B. O'Brien, Maya R. Gupta, Robert M. Gray
ICML (2008), pp. 712719

Functional Bregman Divergence and Bayesian Estimation of Distributions
Bela A. Frigyik, Santosh Srivastava, Maya R. Gupta
IEEE Transactions on Information Theory, vol. 54 (2008), pp. 51305139

Functional Bregman divergence
Bela A. Frigyik, Santosh Srivastava, Maya R. Gupta
ISIT (2008), pp. 16811685

Generative models for similaritybased classification
Luca Cazzanti, Maya R. Gupta, Anjali J. Koppal
Pattern Recognition, vol. 41 (2008), pp. 22892297

Learning custom color transformations with adaptive neighborhoods
Maya R. Gupta, Eric K. Garcia, Andrey Stroilov
J. Electronic Imaging, vol. 17 (2008), pp. 033005

Multiresolutional regularization of local linear regression over adaptive neighborhoods for color management
Nasiha Hrustemovic, Maya R. Gupta
ICIP (2008), pp. 497500

An EM Technique for Multiple Transmitter Localization
Jill K. Nelson, Maya R. Gupta
CISS (2007), pp. 610615

Bayesian Quadratic Discriminant Analysis
Santosh Srivastava, Maya R. Gupta, Bela A. Frigyik
Journal of Machine Learning Research, vol. 8 (2007), pp. 12771305

Color Management of Printers by Regression over Enclosing Neighborhoods
Erika M. Chin, Eric K. Garcia, Maya R. Gupta
ICIP (2) (2007), pp. 161164

Linear Fusion of Image Sets for Display
Nathaniel P. Jacobson, Maya R. Gupta, Jeff B. Cole
IEEE T. Geoscience and Remote Sensing, vol. 45 (2007), pp. 32773288

Local similarity discriminant analysis
Luca Cazzanti, Maya R. Gupta
ICML (2007), pp. 137144

OCR binarization and image preprocessing for searching historical documents
Maya R. Gupta, Nathaniel P. Jacobson, Eric K. Garcia
Pattern Recognition, vol. 40 (2007), pp. 389397

SNRAdaptive Linear Fusion of Hyperspectral Images for Color Display
Nathaniel P. Jacobson, Maya R. Gupta
ICIP (3) (2007), pp. 477480

Functional Bregman Divergence and Bayesian Estimation of Distributions
Bela A. Frigyik, Santosh Srivastava, Maya R. Gupta
CoRR, vol. abs/cs/0611123 (2006)

Nonparametric Supervised Learning by Linear Interpolation with Maximum Entropy
Maya R. Gupta, Robert M. Gray, Richard A. Olshen
IEEE Trans. Pattern Anal. Mach. Intell., vol. 28 (2006), pp. 766781

Wavelet Principal Component Analysis and its Application to Hyperspectral Images
Maya R. Gupta, Nathaniel P. Jacobson
ICIP (2006), pp. 15851588

Custom color enhancements by statistical learning
ICIP (3) (2005), pp. 968971

Design goals and solutions for display of hyperspectral images
Nathaniel P. Jacobson, Maya R. Gupta
IEEE T. Geoscience and Remote Sensing, vol. 43 (2005), pp. 26842692

Design goals and solutions for display of hyperspectral images
Nathaniel P. Jacobson, Maya R. Gupta
ICIP (2) (2005), pp. 622625

Color conversions using maximum entropy estimation
Maya R. Gupta, Robert M. Gray
ICIP (1) (2001), pp. 118121

Block Color Quantization: A New Method for Color Halftoning
Maya R. Gupta, Michael J. Gormish, David G. Stork
ICIP (2000), pp. 460463