| Transferable Perturbations of Deep Feature Distributions N Inkawhich, KJ Liang, L Carin, Y Chen International Conference on Learning Representations, 2020 | 53 | 2020 |
| 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 | 45 | 2020 |
| 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 | 41 | 2018 |
| 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 | 34 | 2018 |
| 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 | 26 | 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 | 26 | 2021 |
| Object Detection as a Positive-Unlabeled Problem Y Yang, KJ Liang, L Carin British Machine Vision Conference, 2020 | 23 | 2020 |
| 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 | 23 | 2020 |
| 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 | 22 | 2021 |
| 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 | 21* | 2021 |
| 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 | 18 | 2021 |
| Few-shot Learning with Noisy Labels KJ Liang, SB Rangrej, V Petrovic, T Hassner Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 10 | 2022 |
| 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 | 9 | 2020 |
| Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection L Yin, JM Perez-Rua, KJ Liang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 8 | 2022 |
| WAFFLe: Weight Anonymized Factorization for Federated Learning W Hao, N Mehta, KJ Liang, P Cheng, M El-Khamy, L Carin IEEE Access, 2022 | 7 | 2022 |
| 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 | 7 | 2019 |
| Extending One-Stage Detection with Open-World Proposals S Konan, KJ Liang, L Yin arXiv preprint arXiv:2201.02302, 2022 | 6 | 2022 |
| 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 | 3 | 2021 |
| 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 | 2 | 2021 |
| GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action Prediction SB Rangrej, KJ Liang, T Hassner, JJ Clark Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 1 | 2023 |
Lawrence CarinProvost, King Abdullah University of Science & Technology (KAUST)kaust.edu.sa의 이메일 확인됨
