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MixKD: Towards Efficient Distillation of Large-scale Language Models

Nov 01, 2020
Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin


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Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images

Oct 02, 2020
John B. Sigman, Gregory P. Spell, Kevin J Liang, Lawrence Carin

* Proc. SPIE 11404, Anomaly Detection and Imaging with X-Rays (ADIX) V, 1140404 (26 May 2020) 

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WAFFLe: Weight Anonymized Factorization for Federated Learning

Aug 13, 2020
Weituo Hao, Nikhil Mehta, Kevin J Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin


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Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability

Apr 29, 2020
Nathan Inkawhich, Kevin J Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen


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Transferable Perturbations of Deep Feature Distributions

Apr 27, 2020
Nathan Inkawhich, Kevin J Liang, Lawrence Carin, Yiran Chen

* Published as a conference paper at ICLR 2020 

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Bayesian Nonparametric Weight Factorization for Continual Learning

Apr 21, 2020
Nikhil Mehta, Kevin J Liang, Lawrence Carin


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Object Detection as a Positive-Unlabeled Problem

Feb 11, 2020
Yuewei Yang, Kevin J Liang, Lawrence Carin


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Toward Automatic Threat Recognition for Airport X-ray Baggage Screening with Deep Convolutional Object Detection

Dec 13, 2019
Kevin J Liang, John B. Sigman, Gregory P. Spell, Dan Strellis, William Chang, Felix Liu, Tejas Mehta, Lawrence Carin


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Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods

Oct 09, 2019
Kevin J Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin


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Generative Adversarial Network Training is a Continual Learning Problem

Nov 27, 2018
Kevin J Liang, Chunyuan Li, Guoyin Wang, Lawrence Carin


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