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Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning.

J. Zhang, B. Kailkhura, and T. Han. ICML, volume 119 of Proceedings of Machine Learning Research, page 11117-11128. PMLR, (2020)

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Data Falsification Attacks on Consensus-Based Detection Systems.B. Kailkhura, S. Brahma, and P. Varshney. IEEE Trans. Signal and Information Processing over Networks, 3 (1): 145-158 (2017)MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense.R. Anirudh, J. Thiagarajan, B. Kailkhura, and T. Bremer. CoRR, (2018)Automatic Perturbation Analysis on General Computational Graphs.K. Xu, Z. Shi, H. Zhang, M. Huang, K. Chang, B. Kailkhura, X. Lin, and C. Hsieh. CoRR, (2020)MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific Data.Q. Li, B. Kailkhura, R. Anirudh, J. Zhang, Y. Zhou, Y. Liang, T. Han, and P. Varshney. SIAM J. Math. Data Sci., 3 (4): 1197-1222 (2021)Neural Image Compression: Generalization, Robustness, and Spectral Biases.K. Lieberman, J. Diffenderfer, C. Godfrey, and B. Kailkhura. CoRR, (2023)Robust Federated Learning Using ADMM in the Presence of Data Falsifying Byzantines.Q. Li, B. Kailkhura, R. Goldhahn, P. Ray, and P. Varshney. CoRR, (2017)Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation.H. Zheng, J. Sun, S. Wu, B. Kailkhura, Z. Mao, C. Xiao, and A. Prakash. CoRR, (2023)DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training.A. Chen, Y. Zhang, J. Jia, J. Diffenderfer, J. Liu, K. Parasyris, Y. Zhang, Z. Zhang, B. Kailkhura, and S. Liu. CoRR, (2023)Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning.A. Mallick, C. Dwivedi, B. Kailkhura, G. Joshi, and T. Han. CoRR, (2020)COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks.F. Wu, L. Li, C. Xu, H. Zhang, B. Kailkhura, K. Kenthapadi, D. Zhao, and B. Li. CoRR, (2022)

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Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning.

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Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning.