Recent advances in terahertz imaging DM Mittleman, M Gupta, R Neelamani, RG Baraniuk, JV Rudd, M Koch Applied Physics B 68, 1085-1094, 1999 | 1030 | 1999 |
Theory and use of the EM algorithm MR Gupta, Y Chen Foundations and Trends® in Signal Processing 4 (3), 223-296, 2011 | 654* | 2011 |
To trust or not to trust a classifier H Jiang, B Kim, M Guan, M Gupta Advances in neural information processing systems 31, 2018 | 542 | 2018 |
Similarity-based classification: Concepts and algorithms. Y Chen, EK Garcia, MR Gupta, A Rahimi, L Cazzanti Journal of Machine Learning Research 10 (3), 2009 | 494 | 2009 |
OCR binarization and image pre-processing for searching historical documents MR Gupta, NP Jacobson, EK Garcia Pattern Recognition 40 (2), 389-397, 2007 | 317 | 2007 |
Bayesian quadratic discriminant analysis. S Srivastava, MR Gupta, BA Frigyik Journal of Machine Learning Research 8 (6), 2007 | 314 | 2007 |
Introduction to the Dirichlet distribution and related processes BA Frigyik, A Kapila, MR Gupta Department of Electrical Engineering, University of Washignton, UWEETR-2010 …, 2010 | 269 | 2010 |
Satisfying real-world goals with dataset constraints G Goh, A Cotter, M Gupta, MP Friedlander Advances in neural information processing systems 29, 2016 | 256 | 2016 |
How to analyze paired comparison data K Tsukida, MR Gupta Department of Electrical Engineering University of Washington, Tech. Rep …, 2011 | 224 | 2011 |
Deep lattice networks and partial monotonic functions S You, D Ding, K Canini, J Pfeifer, M Gupta Advances in neural information processing systems 30, 2017 | 190 | 2017 |
Design goals and solutions for display of hyperspectral images NP Jacobson, MR Gupta IEEE Transactions on Geoscience and Remote Sensing 43 (11), 2684-2692, 2005 | 187 | 2005 |
Optimization with non-differentiable constraints with applications to fairness, recall, churn, and other goals A Cotter, H Jiang, M Gupta, S Wang, T Narayan, S You, K Sridharan Journal of Machine Learning Research 20 (172), 1-59, 2019 | 177 | 2019 |
Monotonic calibrated interpolated look-up tables M Gupta, A Cotter, J Pfeifer, K Voevodski, K Canini, A Mangylov, ... Journal of Machine Learning Research 17 (109), 1-47, 2016 | 162 | 2016 |
Functional Bregman divergence and Bayesian estimation of distributions BA Frigyik, S Srivastava, MR Gupta IEEE Transactions on Information Theory 54 (11), 5130-5139, 2008 | 155* | 2008 |
Robust optimization for fairness with noisy protected groups S Wang, W Guo, H Narasimhan, A Cotter, M Gupta, M Jordan Advances in neural information processing systems 33, 5190-5203, 2020 | 140 | 2020 |
Training highly multiclass classifiers MR Gupta, S Bengio, J Weston The Journal of Machine Learning Research 15 (1), 1461-1492, 2014 | 130 | 2014 |
Pairwise fairness for ranking and regression H Narasimhan, A Cotter, M Gupta, S Wang Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5248-5255, 2020 | 128 | 2020 |
Training well-generalizing classifiers for fairness metrics and other data-dependent constraints A Cotter, M Gupta, H Jiang, N Srebro, K Sridharan, S Wang, B Woodworth, ... International Conference on Machine Learning, 1397-1405, 2019 | 120 | 2019 |
Linear fusion of image sets for display NP Jacobson, MR Gupta, JB Cole IEEE Transactions on Geoscience and Remote Sensing 45 (10), 3277-3288, 2007 | 99 | 2007 |
Deep k-nn for noisy labels D Bahri, H Jiang, M Gupta International Conference on Machine Learning, 540-550, 2020 | 88 | 2020 |