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Kevin J Liang
Kevin J Liang
Research Scientist @ Facebook
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Generative Adversarial Network Training is a Continual Learning Problem
KJ Liang, C Li, G Wang, L Carin
Neural Information Processing Systems, Continual Learning Workshop, 2018
352018
Transferable Perturbations of Deep Feature Distributions
N Inkawhich, KJ Liang, L Carin, Y Chen
International Conference on Learning Representations, 2020
322020
Automatic Threat Recognition of Prohibited Items at Aviation Checkpoints with X-ray Imaging: A Deep Learning Approach
KJ Liang, G Heilmann, C Gregory, SO Diallo, D Carlson, GP Spell, ...
Anomaly Detection and Imaging with X-Rays (ADIX) III 10632, 1063203, 2018
262018
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
N Inkawhich, KJ Liang, B Wang, M Inkawhich, L Carin, Y Chen
Advances in Neural Information Processing Systems, 20791-20801, 2020
252020
Object Detection as a Positive-Unlabeled Problem
Y Yang, KJ Liang, L Carin
British Machine Vision Conference, 2020
172020
Toward Automatic Threat Recognition for Airport X-ray Baggage Screening with Deep Convolutional Object Detection
KJ Liang, JB Sigman, GP Spell, D Strellis, W Chang, F Liu, T Mehta, ...
Denver X-ray Conference, 2020
172020
Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors
N Mehta, K Liang, VK Verma, L Carin
International Conference on Artificial Intelligence and Statistics, 100-108, 2021
12*2021
MixKD: Towards Efficient Distillation of Large-scale Language Models
KJ Liang, W Hao, D Shen, Y Zhou, W Chen, C Chen, L Carin
International Conference on Learning Representations, 2021
112021
A Multiplexed Network for End-to-end, Multilingual OCR
J Huang, G Pang, R Kovvuri, M Toh, KJ Liang, P Krishnan, X Yin, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
92021
Efficient Feature Transformations for Discriminative and Generative Continual Learning
VK Verma, KJ Liang, N Mehta, P Rai, L Carin
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
82021
Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-ray Images
JB Sigman, GP Spell, KJ Liang, L Carin
Anomaly Detection and Imaging with X-Rays (ADIX) V 11404, 1140404, 2020
62020
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
K Liang, G Wang, Y Li, R Henao, L Carin
Advances in Neural Information Processing Systems, 3392-3403, 2019
62019
Towards Fair Federated Learning with Zero-Shot Data Augmentation
W Hao, M El-Khamy, J Lee, J Zhang, KJ Liang, C Chen, L Carin
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
52021
WAFFLe: Weight Anonymized Factorization for Federated Learning
W Hao, N Mehta, KJ Liang, P Cheng, M El-Khamy, L Carin
IEEE Access, 2022
42022
Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning
VK Verma, K Liang, N Mehta, L Carin
arXiv preprint arXiv:2102.11856, 2021
32021
Few-shot Learning with Noisy Labels
KJ Liang, SB Rangrej, V Petrovic, T Hassner
arXiv preprint arXiv:2204.05494, 2022
12022
Extending One-Stage Detection with Open-World Proposals
S Konan, KJ Liang, L Yin
arXiv preprint arXiv:2201.02302, 2022
12022
Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap?
N Inkawhich, KJ Liang, J Zhang, H Yang, H Li, Y Chen
Proceedings of the IEEE/CVF International Conference on Computer Vision, 41-50, 2021
12021
Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection
L Yin, JM Perez-Rua, KJ Liang
arXiv preprint arXiv:2203.13903, 2022
2022
Revisiting Linear Decision Boundaries for Few-Shot Learning with Transformer Hypernetworks
SB Rangrej, KJ Liang, X Yin, G Pang, T Karaletsos, L Wolf, T Hassner
2021
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학술자료 1–20