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Saehoon Kim
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2020 – today
- 2023
- [c25]Chiheon Kim, Doyup Lee, Saehoon Kim, Minsu Cho, Wook-Shin Han:
Generalizable Implicit Neural Representations via Instance Pattern Composers. CVPR 2023: 11808-11817 - [c24]Minsoo Kang, Doyup Lee, Jiseob Kim, Saehoon Kim, Bohyung Han:
Variational Distribution Learning for Unsupervised Text-to-Image Generation. CVPR 2023: 23380-23389 - [i17]Minsoo Kang, Doyup Lee, Jiseob Kim, Saehoon Kim, Bohyung Han:
Variational Distribution Learning for Unsupervised Text-to-Image Generation. CoRR abs/2303.16105 (2023) - 2022
- [c23]Youhan Lee, Kyungtae Lim, Woonhyuk Baek, Byungseok Roh, Saehoon Kim:
Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss. COLING 2022: 5730-5744 - [c22]Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, Wook-Shin Han:
Autoregressive Image Generation using Residual Quantization. CVPR 2022: 11513-11522 - [c21]Byungseok Roh, Jaewoong Shin, Wuhyun Shin, Saehoon Kim:
Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity. ICLR 2022 - [c20]Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, Wook-Shin Han:
Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer. NeurIPS 2022 - [c19]Tackgeun You, Saehoon Kim, Chiheon Kim, Doyup Lee, Bohyung Han:
Locally Hierarchical Auto-Regressive Modeling for Image Generation. NeurIPS 2022 - [i16]Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, Wook-Shin Han:
Autoregressive Image Generation using Residual Quantization. CoRR abs/2203.01941 (2022) - [i15]Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, Wook-Shin Han:
Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer. CoRR abs/2206.04452 (2022) - [i14]Chiheon Kim, Doyup Lee, Saehoon Kim, Minsu Cho, Wook-Shin Han:
Generalizable Implicit Neural Representations via Instance Pattern Composers. CoRR abs/2211.13223 (2022) - 2021
- [j3]Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, Seungjin Choi:
Bayesian optimization with approximate set kernels. Mach. Learn. 110(5): 857-879 (2021) - [i13]Saehoon Kim, Sungwoong Kim, Juho Lee:
Hybrid Generative-Contrastive Representation Learning. CoRR abs/2106.06162 (2021) - [i12]Chiheon Kim, Saehoon Kim, Jongmin Kim, Donghoon Lee, Sungwoong Kim:
Automated Learning Rate Scheduler for Large-batch Training. CoRR abs/2107.05855 (2021) - [i11]Byungseok Roh, Jaewoong Shin, Wuhyun Shin, Saehoon Kim:
Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity. CoRR abs/2111.14330 (2021) - 2020
- [c18]Ingyo Chung, Saehoon Kim, Juho Lee, Kwang Joon Kim, Sung Ju Hwang, Eunho Yang:
Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare. AAAI 2020: 3649-3657 - [c17]Haebeom Lee, Hayeon Lee, Donghyun Na, Saehoon Kim, Minseop Park, Eunho Yang, Sung Ju Hwang:
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks. ICLR 2020 - [c16]Jaehong Yoon, Saehoon Kim, Eunho Yang, Sung Ju Hwang:
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition. ICLR 2020
2010 – 2019
- 2019
- [c15]Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, Eunho Yang, Sung Ju Hwang, Yi Yang:
Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning. ICLR (Poster) 2019 - [i10]Jaehong Yoon, Saehoon Kim, Eunho Yang, Sung Ju Hwang:
ORACLE: Order Robust Adaptive Continual LEarning. CoRR abs/1902.09432 (2019) - [i9]Minseop Park, Jungtaek Kim, Saehoon Kim, Yanbin Liu, Seungjin Choi:
MxML: Mixture of Meta-Learners for Few-Shot Classification. CoRR abs/1904.05658 (2019) - [i8]Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, Seungjin Choi:
Bayesian Optimization over Sets. CoRR abs/1905.09780 (2019) - [i7]Donghyun Na, Haebeom Lee, Saehoon Kim, Minseop Park, Eunho Yang, Sung Ju Hwang:
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks. CoRR abs/1905.12917 (2019) - 2018
- [j2]Saehoon Kim, Seungjin Choi:
Sparse Circulant Binary Embedding: An Asymptotic Analysis. IEEE Signal Process. Lett. 25(3): 432-436 (2018) - [c14]Yoonho Hwang, Mooyeol Baek, Saehoon Kim, Bohyung Han, Hee-Kap Ahn:
Product Quantized Translation for Fast Nearest Neighbor Search. AAAI 2018: 3295-3301 - [c13]Saehoon Kim, Jungtaek Kim, Seungjin Choi:
On the Optimal Bit Complexity of Circulant Binary Embedding. AAAI 2018: 3423-3430 - [c12]Jay Heo, Haebeom Lee, Saehoon Kim, Juho Lee, Kwang Joon Kim, Eunho Yang, Sung Ju Hwang:
Uncertainty-Aware Attention for Reliable Interpretation and Prediction. NeurIPS 2018: 917-926 - [c11]Haebeom Lee, Juho Lee, Saehoon Kim, Eunho Yang, Sung Ju Hwang:
DropMax: Adaptive Variational Softmax. NeurIPS 2018: 927-937 - [i6]Jay Heo, Haebeom Lee, Saehoon Kim, Juho Lee, Kwang Joon Kim, Eunho Yang, Sung Ju Hwang:
Uncertainty-Aware Attention for Reliable Interpretation and Prediction. CoRR abs/1805.09653 (2018) - [i5]Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, Yi Yang:
Transductive Propagation Network for Few-shot Learning. CoRR abs/1805.10002 (2018) - [i4]Juho Lee, Saehoon Kim, Jaehong Yoon, Haebeom Lee, Eunho Yang, Sung Ju Hwang:
Adaptive Network Sparsification via Dependent Variational Beta-Bernoulli Dropout. CoRR abs/1805.10896 (2018) - [i3]Ingyo Chung, Saehoon Kim, Juho Lee, Sung Ju Hwang, Eunho Yang:
Mixed Effect Composite RNN-GP: A Personalized and Reliable Prediction Model for Healthcare. CoRR abs/1806.01551 (2018) - 2017
- [c10]Saehoon Kim, Seungjin Choi:
Binary Embedding with Additive Homogeneous Kernels. AAAI 2017: 2094-2100 - [i2]Jungtaek Kim, Saehoon Kim, Seungjin Choi:
Learning to Transfer Initializations for Bayesian Hyperparameter Optimization. CoRR abs/1710.06219 (2017) - 2016
- [j1]Seung-won Hwang, Saehoon Kim, Yuxiong He, Sameh Elnikety, Seungjin Choi:
Prediction and Predictability for Search Query Acceleration. ACM Trans. Web 10(3): 19:1-19:28 (2016) - 2015
- [c9]Saehoon Kim, Seungjin Choi:
Bilinear random projections for locality-sensitive binary codes. CVPR 2015: 1338-1346 - [c8]Saehoon Kim, Xin-Jing Wang, Lei Zhang, Seungjin Choi:
Near Duplicate Image Discovery on One Billion Images. WACV 2015: 943-950 - [c7]Saehoon Kim, Yuxiong He, Seung-won Hwang, Sameh Elnikety, Seungjin Choi:
Delayed-Dynamic-Selective (DDS) Prediction for Reducing Extreme Tail Latency in Web Search. WSDM 2015: 7-16 - [i1]Saehoon Kim, Seungjin Choi:
Bilinear Random Projections for Locality-Sensitive Binary Codes. CoRR abs/1506.01092 (2015) - 2014
- [c6]Myeongjae Jeon, Saehoon Kim, Seung-won Hwang, Yuxiong He, Sameh Elnikety, Alan L. Cox, Scott Rixner:
Predictive parallelization: taming tail latencies in web search. SIGIR 2014: 253-262 - 2013
- [c5]Saehoon Kim, Seungjin Choi:
Multi-view anchor graph hashing. ICASSP 2013: 3123-3127 - 2012
- [c4]Saehoon Kim, Yoonseop Kang, Seungjin Choi:
Sequential Spectral Learning to Hash with Multiple Representations. ECCV (5) 2012: 538-551 - [c3]Yoonseop Kang, Saehoon Kim, Seungjin Choi:
Deep Learning to Hash with Multiple Representations. ICDM 2012: 930-935 - [c2]Jeong-Min Yun, Saehoon Kim, Seungjin Choi:
Hashing with Generalized Nyström Approximation. ICDM 2012: 1188-1193 - 2011
- [c1]Saehoon Kim, Seungjin Choi:
Semi-supervised Discriminant Hashing. ICDM 2011: 1122-1127
Coauthor Index
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