Semi-supervised Discriminant Hashing. - Saehoon Kim; Seungjin Choi (ICDM, 2011)

Sequential Spectral Learning to Hash with Multiple Representations. - Saehoon Kim; Yoonseop Kang; Seungjin Choi (ECCV (5), 2012)

Deep Learning to Hash with Multiple Representations. - Yoonseop Kang; Saehoon Kim; Seungjin Choi (ICDM, 2012)

Hashing with Generalized Nyström Approximation. - Jeong-Min Yun; Saehoon Kim; Seungjin Choi (ICDM, 2012)

Multi-view anchor graph hashing. - Saehoon Kim; Seungjin Choi (ICASSP, 2013)

Predictive parallelization: taming tail latencies in web search. - Myeongjae Jeon; Saehoon Kim; Seung-won Hwang; Yuxiong He; Sameh Elnikety; Alan L. Cox; Scott Rixner (SIGIR, 2014)

Bilinear random projections for locality-sensitive binary codes. - Saehoon Kim; Seungjin Choi (CVPR, 2015)

Near Duplicate Image Discovery on One Billion Images. - Saehoon Kim; Xin-Jing Wang; Lei Zhang 001; Seungjin Choi (WACV, 2015)

Delayed-Dynamic-Selective (DDS) Prediction for Reducing Extreme Tail Latency in Web Search. - Saehoon Kim; Yuxiong He; Seung-won Hwang; Sameh Elnikety; Seungjin Choi (WSDM, 2015)

Prediction and Predictability for Search Query Acceleration. - Seung-won Hwang; Saehoon Kim; Yuxiong He; Sameh Elnikety; Seungjin Choi (ACM Trans. Web, 2016)

Binary Embedding with Additive Homogeneous Kernels. - Saehoon Kim; Seungjin Choi (AAAI, 2017)

Learning to Transfer Initializations for Bayesian Hyperparameter Optimization. - Jungtaek Kim 001; Saehoon Kim; Seungjin Choi (CoRR, 2017)

Product Quantized Translation for Fast Nearest Neighbor Search. - Yoonho Hwang; Mooyeol Baek; Saehoon Kim; Bohyung Han; Hee-Kap Ahn (AAAI, 2018)

On the Optimal Bit Complexity of Circulant Binary Embedding. - Saehoon Kim; Jungtaek Kim 001; Seungjin Choi (AAAI, 2018)

Uncertainty-Aware Attention for Reliable Interpretation and Prediction. - Jay Heo; Haebeom Lee; Saehoon Kim; Juho Lee 001; Kwang Joon Kim; Eunho Yang; Sung Ju Hwang (NeurIPS, 2018)

DropMax: Adaptive Variational Softmax. - Haebeom Lee; Juho Lee 001; Saehoon Kim; Eunho Yang; Sung Ju Hwang (NeurIPS, 2018)

Transductive Propagation Network for Few-shot Learning. - Yanbin Liu; Juho Lee 001; Minseop Park; Saehoon Kim; Yi Yang 001 (CoRR, 2018)

Adaptive Network Sparsification via Dependent Variational Beta-Bernoulli Dropout. - Juho Lee 001; Saehoon Kim; Jaehong Yoon; Haebeom Lee; Eunho Yang; Sung Ju Hwang (CoRR, 2018)

Mixed Effect Composite RNN-GP: A Personalized and Reliable Prediction Model for Healthcare. - Ingyo Chung; Saehoon Kim; Juho Lee 001; Sung Ju Hwang; Eunho Yang (CoRR, 2018)

Sparse Circulant Binary Embedding: An Asymptotic Analysis. - Saehoon Kim; Seungjin Choi (IEEE Signal Process. Lett., 2018)

Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning. - Yanbin Liu; Juho Lee 001; Minseop Park; Saehoon Kim; Eunho Yang; Sung Ju Hwang; Yi Yang 001 (ICLR (Poster), 2019)

ORACLE: Order Robust Adaptive Continual LEarning. - Jaehong Yoon; Saehoon Kim; Eunho Yang; Sung Ju Hwang (CoRR, 2019)

MxML: Mixture of Meta-Learners for Few-Shot Classification. - Minseop Park; Jungtaek Kim 001; Saehoon Kim; Yanbin Liu; Seungjin Choi (CoRR, 2019)

Bayesian Optimization over Sets. - Jungtaek Kim 001; Michael McCourt; Tackgeun You; Saehoon Kim; Seungjin Choi (CoRR, 2019)

Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare. - Ingyo Chung; Saehoon Kim; Juho Lee 001; Kwang Joon Kim; Sung Ju Hwang; Eunho Yang (AAAI, 2020)

Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks. - Haebeom Lee; Hayeon Lee; Donghyun Na; Saehoon Kim; Minseop Park; Eunho Yang; Sung Ju Hwang (ICLR, 2020)

Scalable and Order-robust Continual Learning with Additive Parameter Decomposition. - Jaehong Yoon; Saehoon Kim; Eunho Yang; Sung Ju Hwang (ICLR, 2020)

Hybrid Generative-Contrastive Representation Learning. - Saehoon Kim; Sungwoong Kim; Juho Lee 001 (CoRR, 2021)

Automated Learning Rate Scheduler for Large-batch Training. - Chiheon Kim; Saehoon Kim; Jongmin Kim 006; Donghoon Lee; Sungwoong Kim (CoRR, 2021)

Bayesian optimization with approximate set kernels. - Jungtaek Kim 001; Michael McCourt; Tackgeun You; Saehoon Kim; Seungjin Choi (Mach. Learn., 2021)

Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss. - Youhan Lee; Kyungtae Lim; Woonhyuk Baek; Byungseok Roh; Saehoon Kim (COLING, 2022)

Autoregressive Image Generation using Residual Quantization. - Doyup Lee; Chiheon Kim; Saehoon Kim; Minsu Cho; Wook-Shin Han (CVPR, 2022)

Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity. - Byungseok Roh; Jaewoong Shin; Wuhyun Shin; Saehoon Kim (ICLR, 2022)

Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer. - Doyup Lee; Chiheon Kim; Saehoon Kim; Minsu Cho; Wook-Shin Han (NeurIPS, 2022)

Locally Hierarchical Auto-Regressive Modeling for Image Generation. - Tackgeun You; Saehoon Kim; Chiheon Kim; Doyup Lee; Bohyung Han (NeurIPS, 2022)

Variational Distribution Learning for Unsupervised Text-to-Image Generation. - Minsoo Kang; Doyup Lee; Jiseob Kim; Saehoon Kim; Bohyung Han (CVPR, 2023)

Generalizable Implicit Neural Representations via Instance Pattern Composers. - Chiheon Kim; Doyup Lee; Saehoon Kim; Minsu Cho; Wook-Shin Han (CVPR, 2023)

Simulation-Free Training of Neural ODEs on Paired Data. - Semin Kim; Jaehoon Yoo; Jinwoo Kim; Yeonwoo Cha; Saehoon Kim; Seunghoon Hong (NeurIPS, 2024)