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Prudhvi Gurram
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2020 – today
- 2024
- [j12]Taposh Banerjee, Prudhvi Gurram, Gene T. Whipps:
Minimax asymptotically optimal quickest change detection for statistically periodic data. Signal Process. 215: 109290 (2024) - 2021
- [j11]Taposh Banerjee
, Prudhvi Gurram, Gene T. Whipps:
A Bayesian Theory of Change Detection in Statistically Periodic Random Processes. IEEE Trans. Inf. Theory 67(4): 2562-2580 (2021) - 2020
- [c30]Richard Tomsett, Dan Harborne, Supriyo Chakraborty, Prudhvi Gurram, Alun D. Preece:
Sanity Checks for Saliency Metrics. AAAI 2020: 6021-6029 - [c29]Jemin George, Prudhvi Gurram:
Distributed Stochastic Gradient Descent with Event-Triggered Communication. AAAI 2020: 7169-7178 - [c28]Celso M. de Melo, Brandon Rothrock, Prudhvi Gurram, Oytun Ulutan, B. S. Manjunath:
Vision-Based Gesture Recognition in Human-Robot Teams Using Synthetic Data. IROS 2020: 10278-10284 - [c27]Taposh Banerjee, Prudhvi Gurram, Gene T. Whipps:
Multislot and Multistream Quickest Change Detection in Statistically Periodic Processes. ISIT 2020: 1147-1152 - [c26]Anjaly Parayil, He Bai, Jemin George, Prudhvi Gurram:
Decentralized Langevin Dynamics for Bayesian Learning. NeurIPS 2020 - [i13]Liam Hiley, Alun D. Preece, Yulia Hicks, Supriyo Chakraborty, Prudhvi Gurram, Richard Tomsett:
Explaining Motion Relevance for Activity Recognition in Video Deep Learning Models. CoRR abs/2003.14285 (2020) - [i12]Anjaly Parayil, He Bai, Jemin George, Prudhvi Gurram:
A Decentralized Approach to Bayesian Learning. CoRR abs/2007.06799 (2020)
2010 – 2019
- 2019
- [c25]Taposh Banerjee, Prudhvi Gurram, Gene T. Whipps:
A Sequential Detection Theory for Statistically Periodic Random Processes. Allerton 2019: 290-297 - [c24]Jemin George, Tao Yang, He Bai, Prudhvi Gurram:
Distributed Stochastic Gradient Method for Non-Convex Problems with Applications in Supervised Learning. CDC 2019: 5538-5543 - [c23]Taposh Banerjee, Prudhvi Gurram, Gene T. Whipps:
Quickest Detection of Deviations from Periodic Statistical Behavior. ICASSP 2019: 5351-5355 - [c22]Taposh Banerjee, Prudhvi Gurram, Gene T. Whipps:
Bayesian Quickest Detection of Changes in Statistically Periodic Processes. ISIT 2019: 2204-2208 - [i11]Taposh Banerjee, Prudhvi Gurram, Gene T. Whipps:
A Bayesian Theory of Change Detection in Statistically Periodic Random Processes. CoRR abs/1904.03530 (2019) - [i10]Taposh Banerjee, Prudhvi Gurram, Gene T. Whipps:
Quickest Event Detection Using Multimodal Data In Nonstationary Environments. CoRR abs/1904.04239 (2019) - [i9]Jemin George, Tao Yang, He Bai, Prudhvi Gurram:
Distributed Stochastic Gradient Method for Non-Convex Problems with Applications in Supervised Learning. CoRR abs/1908.06693 (2019) - [i8]Jemin George, Prudhvi Gurram:
Distributed Deep Learning with Event-Triggered Communication. CoRR abs/1909.05020 (2019) - [i7]Pengcheng Xu, Prudhvi Gurram, Gene T. Whipps, Rama Chellappa:
Wasserstein Distance Based Domain Adaptation for Object Detection. CoRR abs/1909.08675 (2019) - [i6]Richard Tomsett, Dan Harborne, Supriyo Chakraborty, Prudhvi Gurram, Alun D. Preece:
Sanity Checks for Saliency Metrics. CoRR abs/1912.01451 (2019) - 2018
- [c21]Richard Tomsett, Amy Widdicombe, Tianwei Xing, Supriyo Chakraborty, Simon Julier, Prudhvi Gurram, Raghuveer M. Rao, Mani B. Srivastava
Why the Failure? How Adversarial Examples Can Provide Insights for Interpretable Machine Learning. FUSION 2018: 838-845 - [c20]Taposh Banerjee, Gene T. Whipps, Prudhvi Gurram, Vahid Tarokh:
Sequential Event Detection Using Multimodal Data in Nonstationary Environments. FUSION 2018: 1940-1947 - [c19]Taposh Banerjee, Gene T. Whipps, Prudhvi Gurram, Vahid Tarokh:
Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data. GlobalSIP 2018: 126-130 - [i5]Taposh Banerjee, Gene T. Whipps, Prudhvi Gurram, Vahid Tarokh:
Sequential Event Detection Using Multimodal Data in Nonstationary Environments. CoRR abs/1803.08947 (2018) - [i4]Taposh Banerjee, Gene T. Whipps, Prudhvi Gurram, Vahid Tarokh:
Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data. CoRR abs/1807.06945 (2018) - [i3]Taposh Banerjee, Prudhvi Gurram, Gene T. Whipps:
Quickest Detection Of Deviations From Periodic Statistical Behavior. CoRR abs/1810.12760 (2018) - 2017
- [c18]Supriyo Chakraborty, Richard Tomsett, Ramya Raghavendra, Daniel Harborne, Moustafa Alzantot, Federico Cerutti
Interpretability of deep learning models: A survey of results. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017: 1-6 - 2016
- [j10]Prudhvi Gurram, Heesung Kwon, Charles Davidson:
Coalition Game Theory-Based Feature Subspace Selection for Hyperspectral Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 9(6): 2354-2364 (2016) - [c17]Shuowen Hu, Nathaniel J. Short, Benjamin S. Riggan, Christopher Gordon, Kristan P. Gurton, Matthew Thielke, Prudhvi Gurram, Alex L. Chan:
A Polarimetric Thermal Database for Face Recognition Research. CVPR Workshops 2016: 187-194 - [c16]Tong Wu, Prudhvi Gurram, Raghuveer M. Rao, Waheed U. Bajwa:
Clustering-aware structure-constrained low-rank representation model for learning human action attributes. IVMSP 2016: 1-5 - [p1]Shuowen Hu, Nathaniel J. Short, Prudhvi K. Gurram, Kristan P. Gurton, Christopher Reale:
MWIR-to-Visible and LWIR-to-Visible Face Recognition Using Partial Least Squares and Dictionary Learning. Face Recognition Across the Imaging Spectrum 2016: 69-90 - [i2]Tong Wu, Prudhvi Gurram, Raghuveer M. Rao, Waheed U. Bajwa:
Human Action Attribute Learning From Video Data Using Low-Rank Representations. CoRR abs/1612.07857 (2016) - 2015
- [j9]Zhimin Peng, Prudhvi Gurram, Heesung Kwon, Wotao Yin:
Sparse kernel learning-based feature selection for anomaly detection. IEEE Trans. Aerosp. Electron. Syst. 51(3): 1698-1716 (2015) - [c15]Nathaniel J. Short, Shuowen Hu, Prudhvi Gurram, Kristan P. Gurton:
Exploiting polarization-state information for cross-spectrum face recognition. BTAS 2015: 1-6 - [c14]Tong Wu, Prudhvi Gurram, Raghuveer M. Rao, Waheed U. Bajwa:
Hierarchical Union-of-Subspaces Model for Human Activity Summarization. ICCV Workshops 2015: 1053-1061 - [c13]Prudhvi Gurram, Heesung Kwon, Charles Davidson:
Shapely value based random subspace selection for hyperspectral image classification. IGARSS 2015: 4975-4978 - [i1]Zhimin Peng, Prudhvi Gurram, Heesung Kwon, Wotao Yin:
Optimal Sparse Kernel Learning for Hyperspectral Anomaly Detection. CoRR abs/1506.02585 (2015) - 2014
- [j8]Prudhvi Gurram, Heesung Kwon:
Optimal Sparse Kernel Learning in the Empirical Kernel Feature Space for Hyperspectral Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(4): 1217-1226 (2014) - [c12]Prudhvi Gurram, Raghuveer M. Rao:
Entropy metric regularization for computational imaging with sensor arrays. AIPR 2014: 1-8 - [c11]Prudhvi Gurram, Heesung Kwon:
Coalition game theory based feature subset selection for hyperspectral image classification. IGARSS 2014: 3446-3449 - 2013
- [j7]Heesung Kwon, Xiaofei Hu, James Theiler, Alina Zare
Algorithms for Multispectral and Hyperspectral Image Analysis. J. Electr. Comput. Eng. 2013: 908906:1-908906:2 (2013) - [j6]Prudhvi Gurram, Heesung Kwon:
Contextual SVM Using Hilbert Space Embedding for Hyperspectral Classification. IEEE Geosci. Remote. Sens. Lett. 10(5): 1031-1035 (2013) - [j5]Prudhvi Gurram, Heesung Kwon:
Sparse Kernel-Based Ensemble Learning With Fully Optimized Kernel Parameters for Hyperspectral Classification Problems. IEEE Trans. Geosci. Remote. Sens. 51(2): 787-802 (2013) - [c10]Prudhvi Gurram, Shuowen Hu, Alex L. Chan:
Uniform grid upsampling of 3D lidar point cloud data. Three-Dimensional Image Processing (3DIP) and Applications 2013: 86500B - [c9]Prudhvi Gurram, Heesung Kwon, Zhimin Peng, Wotao Yin:
Optimal sparse kernel learning for hyperspectral anomaly detection. WHISPERS 2013: 1-4 - 2012
- [j4]Prudhvi Gurram, Eli Saber, Harvey E. Rhody:
Semiautomated system for three-dimensional modeling of buildings from aerial video. J. Electronic Imaging 21(1): 013007 (2012) - [j3]Prudhvi Gurram, Heesung Kwon, Timothy Han:
Sparse Kernel-Based Hyperspectral Anomaly Detection. IEEE Geosci. Remote. Sens. Lett. 9(5): 943-947 (2012) - [c8]Prudhvi Gurram, Heesung Kwon:
Contextual SVM for hyperspectral classification using Hilbert Space Embedding. IGARSS 2012: 5470-5473 - [c7]Prudhvi Gurram, Heesung Kwon:
Optimal sparse kernel learning in the Empirical Kernel Feature Space for hyperspectral classification. WHISPERS 2012: 1-4 - 2011
- [j2]Prudhvi Gurram, Heesung Kwon:
Support-Vector-Based Hyperspectral Anomaly Detection Using Optimized Kernel Parameters. IEEE Geosci. Remote. Sens. Lett. 8(6): 1060-1064 (2011) - [c6]Prudhvi Gurram, Heesung Kwon:
Generalized optimal Kernel-Based Ensemble Learning for hyperspectral classification problems. IGARSS 2011: 4431-4434 - [c5]Prudhvi Gurram, Heesung Kwon:
Hyperspectral anomaly detection using an optimized support vector data description method. WHISPERS 2011: 1-4 - 2010
- [j1]Prudhvi Gurram, Eli Saber, Harvey E. Rhody:
A Segment-Based Mesh Design for Building Parallel-Perspective Stereo Mosaics. IEEE Trans. Geosci. Remote. Sens. 48(3-1): 1256-1269 (2010) - [c4]Prudhvi Gurram, Heesung Kwon:
A full diagonal bandwidth gaussian kernel SVM based ensemble learning for hyperspectral chemical plume detection. IGARSS 2010: 2804-2807 - [c3]Heesung Kwon, Prudhvi Gurram:
Optimal kernel bandwidth estimation for hyperspectral kernel-based anomaly detection. IGARSS 2010: 2812-2815
2000 – 2009
- 2009
- [c2]Prudhvi Gurram, Eli Saber, Ferat Sahin, Harvey E. Rhody:
Automated 3D object identification using Bayesian networks. AIPR 2009: 1-8 - 2007
- [c1]Prudhvi Gurram, Stephen R. Lach, Eli Saber, Harvey E. Rhody, John P. Kerekes
3D Scene Reconstruction through a Fusion of Passive Video and Lidar Imagery. AIPR 2007: 133-138
Coauthor Index
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