Maya Gupta

More info and a full list of publications and tutorials can be found here.

Gupta joined Google Research in 2012. Before Google, Gupta was an Associate Professor of Electrical Engineering at the University of Washington (2003-2012), 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

Previous Publications

  •  

    Bounds on the Bayes Error Given Moments

    Bela Frigyik, Maya R. Gupta

    IEEE Trans. Information Theory, vol. 58 (2012), pp. 3606-3612

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    Dimensionality Reduction by Local Discriminative Gaussians

    Nathan Parrish, Maya R. Gupta

    ICML (2012)

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    Multi-Task Averaging

    Sergey Feldman, Maya R. Gupta, Bela A. Frigyik

    NIPS (2012), pp. 1178-1186

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    Optimized Regression for Efficient Function Evaluation

    Eric K. Garcia, Raman Arora, Maya R. Gupta

    IEEE Transactions on Image Processing, vol. 21 (2012), pp. 4128-4140

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    Reliable early classification of time series

    Hyrum S. Anderson, Nathan Parrish, Kristi Tsukida, Maya R. Gupta

    ICASSP (2012), pp. 2073-2076

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    Channel-Robust Classifiers

    Hyrum S. Anderson, Maya R. Gupta, Eric Swanson, Kevin G. Jamieson

    IEEE Transactions on Signal Processing, vol. 59 (2011), pp. 1421-1434

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    Clustering by Left-Stochastic Matrix Factorization

    Raman Arora, Maya R. Gupta, Amol Kapila, Maryam Fazel

    ICML (2011), pp. 761-768

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    Clutter rejection by clustering likelihood-based similarities

    Evan Hanusa, David W. Krout, Maya R. Gupta

    FUSION (2011), pp. 1-6

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    Minimizing bearing bias in tracking by de-coupled rotation and translation estimates

    Raman Arora, Maya R. Gupta

    FUSION (2011), pp. 1-7

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    Completely Lazy Learning

    Eric K. Garcia, Sergey Feldman, Maya R. Gupta, Santosh Srivastava

    IEEE Trans. Knowl. Data Eng., vol. 22 (2010), pp. 1274-1285

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    Estimation of position from multistatic Doppler measurements

    Evan Hanusa, David W. Krout, Maya R. Gupta

    FUSION (2010), pp. 1-7

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    Parametric Bayesian Estimation of Differential Entropy and Relative Entropy

    Maya R. Gupta, Santosh Srivastava

    Entropy, vol. 12 (2010), pp. 818-843

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    Robust sequential classification of tracks

    Nathan Parrish, Hyrum S. Anderson, Maya R. Gupta

    FUSION (2010), pp. 1-8

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    Shadow Dirichlet for Restricted Probability Modeling

    Bela A. Frigyik, Maya R. Gupta, Yihua Chen

    NIPS (2010), pp. 613-621

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    Theory and Use of the EM Algorithm

    Maya R. Gupta, Yihua Chen

    Foundations and Trends in Signal Processing, vol. 4 (2010), pp. 223-296

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    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. 2214-2217

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    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. 354-357

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    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. 2761-2764

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    Filtering web text to match target genres

    Marius A. Marin, Sergey Feldman, Mari Ostendorf, Maya R. Gupta

    ICASSP (2009), pp. 3705-3708

  •  

    Fusing similarities and Euclidean features with generative classifiers

    Luca Cazzanti, Maya R. Gupta, Santosh Srivastava

    FUSION (2009), pp. 224-231

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    Fusing similarities and kernels for classification

    Yihua Chen, Maya R. Gupta

    FUSION (2009), pp. 474-481

  •  

    Gradient estimation in global optimization algorithms

    Megan Hazen, Maya R. Gupta

    IEEE Congress on Evolutionary Computation (2009), pp. 1841-1848

  •  

    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. 594-602

  •  

    Learning kernels from indefinite similarities

    Yihua Chen, Maya R. Gupta, Benjamin Recht

    ICML (2009), pp. 19

  •  

    Part-of-speech histograms for genre classification of text

    Sergey Feldman, Marius A. Marin, Mari Ostendorf, Maya R. Gupta

    ICASSP (2009), pp. 4781-4784

  •  

    Regularizing the Local Similarity Discriminant Analysis Classifier

    Luca Cazzanti, Maya R. Gupta

    ICMLA (2009), pp. 184-189

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    Sequential Bayesian estimation of the probability of detection for tracking

    Kevin G. Jamieson, Maya R. Gupta, David W. Krout

    FUSION (2009), pp. 641-648

  •  

    Similarity-based 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. 747-776

  •  

    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. 936-945

  •  

    Bayesian estimation of the entropy of the multivariate Gaussian

    Santosh Srivastava, Maya R. Gupta

    ISIT (2008), pp. 1103-1107

  •  

    Cost-sensitive multi-class classification from probability estimates

    Deirdre B. O'Brien, Maya R. Gupta, Robert M. Gray

    ICML (2008), pp. 712-719

  •  

    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. 5130-5139

  •  

    Functional Bregman divergence

    Bela A. Frigyik, Santosh Srivastava, Maya R. Gupta

    ISIT (2008), pp. 1681-1685

  •  

    Generative models for similarity-based classification

    Luca Cazzanti, Maya R. Gupta, Anjali J. Koppal

    Pattern Recognition, vol. 41 (2008), pp. 2289-2297

  •  

    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. 497-500

  •  

    An EM Technique for Multiple Transmitter Localization

    Jill K. Nelson, Maya R. Gupta

    CISS (2007), pp. 610-615

  •  

    Bayesian Quadratic Discriminant Analysis

    Santosh Srivastava, Maya R. Gupta, Bela A. Frigyik

    Journal of Machine Learning Research, vol. 8 (2007), pp. 1277-1305

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    Color Management of Printers by Regression over Enclosing Neighborhoods

    Erika M. Chin, Eric K. Garcia, Maya R. Gupta

    ICIP (2) (2007), pp. 161-164

  •  

    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. 3277-3288

  •  

    Local similarity discriminant analysis

    Luca Cazzanti, Maya R. Gupta

    ICML (2007), pp. 137-144

  •  

    OCR binarization and image pre-processing for searching historical documents

    Maya R. Gupta, Nathaniel P. Jacobson, Eric K. Garcia

    Pattern Recognition, vol. 40 (2007), pp. 389-397

  •  

    SNR-Adaptive Linear Fusion of Hyperspectral Images for Color Display

    Nathaniel P. Jacobson, Maya R. Gupta

    ICIP (3) (2007), pp. 477-480

  •  

    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. 766-781

  •  

    Wavelet Principal Component Analysis and its Application to Hyperspectral Images

    Maya R. Gupta, Nathaniel P. Jacobson

    ICIP (2006), pp. 1585-1588

  •  

    Custom color enhancements by statistical learning

    Maya R. Gupta

    ICIP (3) (2005), pp. 968-971

  •  

    Design goals and solutions for display of hyperspectral images

    Nathaniel P. Jacobson, Maya R. Gupta

    ICIP (2) (2005), pp. 622-625

  •  

    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. 2684-2692

  •  

    Color conversions using maximum entropy estimation

    Maya R. Gupta, Robert M. Gray

    ICIP (1) (2001), pp. 118-121

  •  

    Block Color Quantization: A New Method for Color Halftoning

    Maya R. Gupta, Michael J. Gormish, David G. Stork

    ICIP (2000), pp. 460-463