| Learning to propagate labels: Transductive propagation network for few-shot learning Y Liu, J Lee, M Park, S Kim, E Yang, SJ Hwang, Y Yang ICLR 2019, 2019 | 764 | 2019 |
| Predictive parallelization: Taming tail latencies in web search M Jeon, S Kim, S Hwang, Y He, S Elnikety, AL Cox, S Rixner Proceedings of the 37th international ACM SIGIR conference on Research …, 2014 | 120 | 2014 |
| Scalable and order-robust continual learning with additive parameter decomposition J Yoon, S Kim, E Yang, SJ Hwang arXiv preprint arXiv:1902.09432, 2019 | 119 | 2019 |
| Learning to balance: Bayesian meta-learning for imbalanced and out-of-distribution tasks HB Lee, H Lee, D Na, S Kim, M Park, E Yang, SJ Hwang arXiv preprint arXiv:1905.12917, 2019 | 104 | 2019 |
| Uncertainty-aware attention for reliable interpretation and prediction J Heo, HB Lee, S Kim, J Lee, KJ Kim, E Yang, SJ Hwang Advances in neural information processing systems 31, 2018 | 92 | 2018 |
| A deep learning model for real-time mortality prediction in critically ill children SY Kim, S Kim, J Cho, YS Kim, IS Sol, Y Sung, I Cho, M Park, H Jang, ... Critical care 23 (1), 1-10, 2019 | 90 | 2019 |
| Sparse detr: Efficient end-to-end object detection with learnable sparsity B Roh, JW Shin, W Shin, S Kim arXiv preprint arXiv:2111.14330, 2021 | 82 | 2021 |
| Deep learning to hash with multiple representations Y Kang, S Kim, S Choi 2012 IEEE 12th International Conference on Data Mining, 930-935, 2012 | 77 | 2012 |
| Autoregressive image generation using residual quantization D Lee, C Kim, S Kim, M Cho, WS Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 73 | 2022 |
| Delayed-Dynamic-Selective (DDS) prediction for reducing extreme tail latency in web search S Kim, Y He, S Hwang, S Elnikety, S Choi Proceedings of the Eighth ACM International Conference on Web Search and …, 2015 | 70 | 2015 |
| Multi-view anchor graph hashing S Kim, S Choi 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 56 | 2013 |
| Sequential spectral learning to hash with multiple representations S Kim, Y Kang, S Choi Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 54 | 2012 |
| Learning to warm-start Bayesian hyperparameter optimization J Kim, S Kim, S Choi arXiv preprint arXiv:1710.06219, 2017 | 40 | 2017 |
| Semi-supervised discriminant hashing S Kim, S Choi 2011 IEEE 11th International Conference on Data Mining, 1122-1127, 2011 | 37 | 2011 |
| Bilinear random projections for locality-sensitive binary codes S Kim, S Choi Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 24 | 2015 |
| Prediction and predictability for search query acceleration SW Hwang, S Kim, Y He, S Elnikety, S Choi ACM Transactions on the Web (TWEB) 10 (3), 1-28, 2016 | 17 | 2016 |
| DropMax: Adaptive variational softmax HB Lee, J Lee, S Kim, E Yang, SJ Hwang Advances in Neural Information Processing Systems 31, 2018 | 15 | 2018 |
| Near duplicate image discovery on one billion images S Kim, XJ Wang, L Zhang, S Choi 2015 IEEE Winter Conference on Applications of Computer Vision, 943-950, 2015 | 15 | 2015 |
| Draft-and-revise: Effective image generation with contextual rq-transformer D Lee, C Kim, S Kim, M Cho, WS HAN Advances in Neural Information Processing Systems 35, 30127-30138, 2022 | 12 | 2022 |
| Deep mixed effect model using Gaussian processes: a personalized and reliable prediction for healthcare I Chung, S Kim, J Lee, KJ Kim, SJ Hwang, E Yang Proceedings of the AAAI conference on artificial intelligence 34 (04), 3649-3657, 2020 | 12* | 2020 |
Sung Ju HwangKAISTVerified email at kaist.ac.kr
