Publications - MLLAB at SNU

LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging

Jinuk Kim, Marwa El Halabi, Mingi Ji, Hyun Oh Song
International Conference on Machine Learning (ICML), 2024
paper / code / bibtex / project page / poster

Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization

Deokjae Lee, Hyun Oh Song, Kyunghyun Cho
International Conference on Machine Learning (ICML), 2024
paper / code / bibtex

Compressed Context Memory For Online Language Model Interaction

Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun, Hyun Oh Song
International Conference on Learning Representations (ICLR), 2024
paper / code / bibtex / project page

Direct Preference-based Policy Optimization without Reward Modeling

Gaon An*, Junhyeok Lee*, Xingdong Zuo, Norio Kosaka, Kyung-Min Kim, Hyun Oh Song
Neural Information Processing Systems (NeurIPS), 2023
paper / code / bibtex

Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data

Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song
Neural Information Processing Systems (NeurIPS), 2023
paper / code / bibtex

Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning

Seungyong Moon, Junyoung Yeom, Bumsoo Park, Hyun Oh Song
Neural Information Processing Systems (NeurIPS), 2023
paper / code / bibtex

Query-Efficient Black-Box Red Teaming via Bayesian Optimization

Deokjae Lee, JunYeong Lee, Jung-Woo Ha, Jin-Hwa Kim, Sang-Woo Lee, Hwaran Lee, Hyun Oh Song
Association for Computational Linguistics (ACL), 2023
paper / code / bibtex

Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming

Jinuk Kim*, Yeonwoo Jeong*, Deokjae Lee, Hyun Oh Song
International Conference on Machine Learning (ICML), 2023
paper / code / bibtex / blog

Rethinking Value Function Learning for Generalization in Reinforcement Learning

Seungyong Moon, JunYeong Lee, Hyun Oh Song
Neural Information Processing Systems (NeurIPS), 2022
paper / code / bibtex

Dataset Condensation via Efficient Synthetic-Data Parameterization

Jang-Hyun Kim, Jinuk Kim, Seong Joon Oh, Sangdoo Yun, Hwanjun Song, Joonhyun Jeong, Jung-Woo Ha, Hyun Oh Song
International Conference on Machine Learning (ICML), 2022
paper / code / bibtex

Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization

Deokjae Lee, Seungyong Moon, Junhyeok Lee, Hyun Oh Song
International Conference on Machine Learning (ICML), 2022
paper / code / bibtex

Optimal channel selection with discrete QCQP

Yeonwoo Jeong*, Deokjae Lee*, Gaon An, Changyong Son, Hyun Oh Song
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
paper / code / bibtex

Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks

Seungyong Moon*, Gaon An*, Hyun Oh Song
AAAI Conference on Artificial Intelligence (AAAI), 2022
paper / code / bibtex

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

Gaon An*, Seungyong Moon*, Jang-Hyun Kim, Hyun Oh Song
Neural Information Processing Systems (NeurIPS), 2021
paper / code / bibtex

Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity

Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song
International Conference on Learning Representations (ICLR), 2021
Oral (53/2997=1.7%)
paper / code / bibtex

Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup

Jang-Hyun Kim, Wonho Choo, Hyun Oh Song
International Conference on Machine Learning (ICML), 2020
paper / supp / code / bibtex / talk video / blog

End-to-End Efficient Representation Learning via Cascading Combinatorial Optimization

Yeonwoo Jeong, Yoonsung Kim, Hyun Oh Song
IEEE Computer Vision and Pattern Recognition (CVPR), 2019
paper / supp / code / bibtex

Learning Discrete and Continuous Factors of Data via Alternating Disentanglement

Yeonwoo Jeong, Hyun Oh Song
International Conference on Machine Learning (ICML), 2019
paper / supp / code / bibtex / demo / talk video

Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization

Seungyong Moon*, Gaon An*, Hyun Oh Song
International Conference on Machine Learning (ICML), 2019
Long talk (159/3424=4.6%)
paper / supp / code / bibtex / talk video

EMI: Exploration with Mutual Information

Hyoungseok Kim*, Jaekyeom Kim*, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song
International Conference on Machine Learning (ICML), 2019
Long talk (159/3424=4.6%)
paper / supp / code / bibtex / talk video

Efficient end-to-end learning for quantizable representations

Yeonwoo Jeong, Hyun Oh Song
International Conference on Machine Learning (ICML), 2018
Long talk (213/2473=8.6%)
paper / code / bibtex / talk video

Deep Metric Learning via Facility Location

Hyun Oh Song, Stefanie Jegelka, Vivek Rathod, Kevin Murphy
IEEE Computer Vision and Pattern Recognition (CVPR), 2017
Spotlight presentation (144/2680=5.3%)
paper / code / bibtex / talk video

Learning Transferrable Representations for Unsupervised Domain Adaptation

Ozan Sener, Hyun Oh Song, Ashutosh Saxena, Silvio Savarese
Neural Information Processing Systems (NeurIPS), 2016
paper / bibtex

Deep Metric Learning via Lifted Structured Feature Embedding

Hyun Oh Song, Yu Xiang, Stefanie Jegelka, Silvio Savarese
IEEE Computer Vision and Pattern Recognition (CVPR), 2016
Spotlight presentation (123/2145=5.7%)
paper / code / dataset / bibtex / talk video

Generalized Sparselet Models for Real-Time Multiclass Object Recognition

Hyun Oh Song, Ross Girshick, Stefan Zickler, Christopher Geyer, Pedro Felzenszwalb, Trevor Darrell
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015
paper / code / demo video 1 / demo video 2 / bibtex

Learning to detect visual grasp affordance

Hyun Oh Song, Mario Fritz, Daniel Goehring, Trevor Darrell
IEEE Transactions on Automation Science and Engineering (TASE), 2015
paper / demo video / bibtex

Weakly-supervised Discovery of Visual Pattern Configurations

Hyun Oh Song, Yong Jae Lee, Stefanie Jegelka, Trevor Darrell
Neural Information Processing Systems (NeurIPS), 2014
paper / bibtex

On learning to localize objects with minimal supervision

Hyun Oh Song, Ross Girshick, Stefanie Jegelka, Julien Mairal, Zaid Harchaoui, Trevor Darrell
International Conference on Machine Learning (ICML), 2014
paper / talk video / code / bibtex

Discriminatively Activated Sparselets

Hyun Oh Song*, Ross Girshick*, Trevor Darrell
International Conference on Machine Learning (ICML), 2013
Long talk (143/1204=11.8%)
paper / slides / poster / supp / bibtex

Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition

Tim Althoff, Hyun Oh Song, Trevor Darrell
ACM Multimedia (ACMMM), 2012
paper / poster / bibtex

Sparselet Models for Efficient Multiclass Object Detection

Hyun Oh Song, Stefan Zickler, Tim Althoff, Ross Girshick, Mario Fritz, Christopher Geyer, Pedro Felzenszwalb, Trevor Darrell
European Conference on Computer Vision (ECCV), 2012
paper / demo video / poster / bibtex / code