| Learning from simulated and unsupervised images through adversarial training A Shrivastava, T Pfister, O Tuzel, J Susskind, W Wang, R Webb Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1519 | 2017 |
| Multiple kernel learning for sparse representation-based classification A Shrivastava, VM Patel, R Chellappa IEEE Transactions on Image Processing 23 (7), 3013-3024, 2014 | 96 | 2014 |
| Segmenting “simple” objects using RGB-D AK Mishra, A Shrivastava, Y Aloimonos 2012 IEEE International Conference on Robotics and Automation, 4406-4413, 2012 | 66 | 2012 |
| Learning discriminative dictionaries with partially labeled data A Shrivastava, JK Pillai, VM Patel, R Chellappa 2012 19th IEEE International Conference on Image Processing, 3113-3116, 2012 | 50 | 2012 |
| Generalized dictionaries for multiple instance learning A Shrivastava, VM Patel, JK Pillai, R Chellappa International Journal of Computer Vision 114 (2), 288-305, 2015 | 34 | 2015 |
| Unsupervised domain adaptation using parallel transport on Grassmann manifold A Shrivastava, S Shekhar, VM Patel IEEE winter conference on applications of computer vision, 277-284, 2014 | 34 | 2014 |
| Design of non-linear discriminative dictionaries for image classification A Shrivastava, HV Nguyen, VM Patel, R Chellappa Asian Conference on Computer Vision, 660-674, 2012 | 27 | 2012 |
| Divide, denoise, and defend against adversarial attacks SM Moosavi-Dezfooli, A Shrivastava, O Tuzel arXiv preprint arXiv:1802.06806, 2018 | 25 | 2018 |
| Non-linear dictionary learning with partially labeled data A Shrivastava, VM Patel, R Chellappa Pattern Recognition 48 (11), 3283-3292, 2015 | 23 | 2015 |
| Multiple kernel-based dictionary learning for weakly supervised classification A Shrivastava, JK Pillai, VM Patel Pattern Recognition 48 (8), 2667-2675, 2015 | 19 | 2015 |
| Dictionary-based multiple instance learning A Shrivastava, JK Pillai, VM Patel, R Chellappa 2014 IEEE International Conference on Image Processing (ICIP), 160-164, 2014 | 18 | 2014 |
| Class consistent multi-modal fusion with binary features A Shrivastava, M Rastegari, S Shekhar, R Chellappa, LS Davis Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 14 | 2015 |
| Unsupervised style and content separation by minimizing mutual information for speech synthesis TY Hu, A Shrivastava, O Tuzel, C Dhir ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 13 | 2020 |
| Method for generating high-resolution images using regression patterns F Porikli, A Shrivastava, J Thornton US Patent 9,734,558, 2017 | 8 | 2017 |
| Sapaugment: Learning a sample adaptive policy for data augmentation TY Hu, A Shrivastava, JHR Chang, H Koppula, S Braun, K Hwang, ... ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 2 | 2021 |
| Optimize What Matters: Training DNN-Hmm Keyword Spotting Model Using End Metric A Shrivastava, A Kundu, C Dhir, D Naik, O Tuzel ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 1 | 2021 |
| Defense against adversarial attacks on neural networks A Shrivastava, CO Tuzel, S Moosavi-Dezfooli US Patent 10,984,272, 2021 | | 2021 |
| Generating virtual images for promoting visual artificial intelligence K Wang, FY Wang, V Ramesh, A Shrivastava, D Vazquez, F Li Neurocomputing 394, 112-113, 2020 | | 2020 |
| Learning Conditional Error Model for Simulated Time-Series Data. A Shrivastava, O Tuzel CVPR Workshops, 91-94, 2019 | | 2019 |
| Sparse representation, discriminative dictionaries and projections for visual classification A Shrivastava University of Maryland, College Park, 2015 | | 2015 |
