publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2022

  1. NeurIPS
    Locally Hierarchical Auto-Regressive Modeling for Image Generation
    Tackgeun You, Saehoon Kim, Doyup Lee, Chiheon Kim, and Bohyung Han
    In Annual Conference on Neural Information Processing System (NeurIPS),, 2022
  2. NeurIPS
    Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer
    Doyup Lee*, Chiheon Kim*, Saehoon Kim, Minsu Cho, and Wook-Shin Han
    In Annual Conference on Neural Information Processing System (NeurIPS),, 2022
  3. COLING
    Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss
    Youhan Lee, Kyungtae Lim, Woonhyuk Baek, Byungseok Roh, and Saehoon Kim
    In COLING, 2022
  4. CVPR
    Autoregressive Image Generation using Residual Quantization
    Doyup Lee*, Chiheon Kim*, Saehoon Kim, Minsu Cho, and Wook-Shin Han
    In IEEE Conference on Computer Vision and Pattern Recognition (CVPR),, 2022
  5. ICLR
    Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity
    Byungseok Roh*, JaeWoong Shin*, Wuhyun Shin*, and Saehoon Kim
    In International Conference on Learning Representations (ICLR),, 2022

2021

  1. Automated Learning Rate Scheduler for Large-batch Training
    Chiheon Kim, Saehoon Kim, Jongmin Kim, Donghoon Lee, and Sungwoong Kim
    In arXiv preprint arXiv:2107.05855,, 2021
  2. Hybrid Generative-Contrastive Representation Learning
    Saehoon Kim, Sungwoong Kim, and Juho Lee
    In arXiv preprint arXiv:2106.06162,, 2021

2020

  1. ICLR
    Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
    Jaehong Yoon, Saehoon Kim, Eunho Yang, and Sung Ju Hwang
    In International Conference on Learning Representations (ICLR),, 2020

2019

  1. Deep Gaussian Processes for Weakly Supervised Learning: Tumor Mutation Burden (TMB) Prediction
    Sunho Park, Saehoon Kim, Hongmin Xu, and Tae Hyun Hwang
    In NeurIPS 2019 Workshop on Bayesian Deep Learning,, 2019
  2. ICLR
    Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
    Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, Eunho Yang, and 2 more authors
    In International Conference on Learning Representations (ICLR),, 2019
  3. Critical Care
    A Deep Learning Model for Real-time Mortality Prediction in Critically-ill Children
    Soo Yeon Kim*, Saehoon Kim*, Joongbum Cho, In Suk Sol, Youngchul Sung, and 6 more authors
    Critical Care,, 2019
  4. Bayesian Optimization over Sets
    Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, and Seungjin Choi
    In ICML’19 Workshop on Automated Machine Learning,, 2019

2018

  1. TAEML: Task-Adaptive Ensemble of Meta-Learners
    Minseop Park, Saehoon Kim, Jungtaek Kim, Yanbin Liu, and Seungjin Choi
    In NeurIPS’18 Workshop on Meta-Learning,, 2018
  2. Adaptive Network Sparsification with Dependent Variational Beta-Bernoulli Dropout
    Juho Lee, Saehoon Kim, Jaehong Yoon, Hae Beom Lee, Eunho Yang, and 1 more author
    In arXiv preprint arXiv:1805.10896,, 2018
  3. NeurIPS
    DropMax: Adaptive Variational Softmax
    Hae Beom Lee, Juho Lee, Saehoon Kim, Eunho Yang, and Sung Ju Hwang
    In Annual Conference on Neural Information Processing System (NeurIPS),, 2018
  4. NeurIPS
    Uncertainty-Aware Attention for Reliable Interpretation and Prediction
    Jay Heo, Hae Beom Lee, Saehoon Kim, Juho Lee, Kwang Joon Kim, and 2 more authors
    In Annual Conference on Neural Information Processing System (NeurIPS),, 2018
  5. Sparse Circulant Binary Embedding: An Asymptotic Analysis
    Saehoon Kim, and Seungjin Choi
    IEEE Signal Processing Letters,, 2018
  6. AAAI
    On the Optimal Bit Complexity of Circulant Binary Embedding
    Saehoon Kim, Jungtaek Kim, and Seungjin Choi
    In AAAI Conference on Artificial Intelligence (AAAI),, 2018
  7. AAAI
    Product Qunatized Translations for Fast Nearest Neighbor Search
    Yoonho Hwang, Moo-yeol Baek, Saehoon Kim, Bohyung Han, and Hee-kap Ahn
    In AAAI Conference on Artificial Intelligence (AAAI),, 2018

2017

  1. AAAI
    Binary Embedding with Additive Homogeneous Kernels
    Saehoon Kim, and Seungjin Choi
    In AAAI Conference on Artificial Intelligence (AAAI),, 2017
  2. Learning to Transfer Initializations for Bayesian Hyperparameter Optimization
    Jungtaek Kim, Saehoon Kim, and Seungjin Choi
    In NeurIPS’17 Workshop on Bayesian Optimization,, 2017

2016

  1. Prediction and Predictability for Search Query Acceleration
    Seungwon Hwang, Saehoon Kim, Yuxiong He, Sameh Elnikety, and Seungjin Choi
    ACM Transcations on the Web,, 2016

2015

  1. CVPR
    Bilinear Random Projections for Locality-Sensitive Binary Codes
    Saehoon Kim, and Seungjin Choi
    In IEEE Conference on Computer Vision and Pattern Recognition (CVPR),, 2015
  2. WSDM
    DDS Prediction: Reducing Extreme Tail Latency in Web Search
    Saehoon Kim, Yuxiong He, Seungwon Hwang, Sameh Elnikety, and Seungjin Choi
    In ACM International WSDM Conference (WSDM),, 2015
  3. WACV
    Near-Duplicate Image Discovery on One Billion Images
    Saehoon Kim, Xin-Jing Wang, Lei Zhang, and Seungjin Choi
    In IEEE Winter Conference on Applications of Computer Vision (WACV),, 2015

2014

  1. SIGIR
    Predictive Parallelization: Taming Tail Latencies in Web Search
    Myeongjae Jeon, Saehoon Kim, Seung-won Hwang, Yuxiong He, Sameh Elnikety, and 2 more authors
    In ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR),, 2014

2013

  1. ICASSP
    Multi-view Anchor Graph Hashing
    Saehoon Kim, and Seungjin Choi
    In IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP),, 2013

2012

  1. ICDM
    Hashing with Generalized Nyström Approximation
    Jeong-Min Yun, Saehoon Kim, and Seungjin Choi
    In IEEE International Conference on Data Mining (ICDM),, 2012
  2. ICDM
    Deep Learning to Hash with Multiple Representations
    Yoonseop Kang, Saehoon Kim, and Seungjin Choi
    In IEEE International Conference on Data Mining (ICDM),, 2012
  3. ECCV
    Sequential Spectral Learning to Hash with Multiple Representations
    Saehoon Kim, Yoonseop Kang, and Seungjin Choi
    In European Conference on Computer Vision (ECCV),, 2012

2011

  1. ICDM
    Semi-Supervised Discriminant Hashing
    Saehoon Kim, and Seungjin Choi
    In IEEE International Conference on Data Mining (ICDM),, 2011

2010

  1. Local Dimensionality Reduction for Multiple Instance Learning
    Saehoon Kim, and Seungjin Choi
    In IEEE International Workshop on Machine Learning for Signal Processing,, 2010