Hyun Oh Song

According to our database, Hyun Oh Song authored at least 38 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Compressed Context Memory For Online Language Model Interaction.

Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun, Hyun Oh Song

CoRR, 2023

Designing an offline reinforcement learning objective from scratch.

Gaon An, Junhyeok Lee, Xingdong Zuo, Norio Kosaka, Kyung-Min Kim, Hyun Oh Song

CoRR, 2023

Neural Relation Graph for Identifying Problematic Data.

Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song

CoRR, 2023

Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning.

Seungyong Moon, Junyoung Yeom, Bumsoo Park, Hyun Oh Song

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Direct Preference-based Policy Optimization without Reward Modeling.

Gaon An, Junhyeok Lee, Xingdong Zuo, Norio Kosaka, Kyung-Min Kim, Hyun Oh Song

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Jinuk Kim, Yeonwoo Jeong, Deokjae Lee, Hyun Oh Song

Proceedings of the International Conference on Machine Learning, 2023

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

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Rethinking Value Function Learning for Generalization in Reinforcement Learning.

Seungyong Moon, JunYeong Lee, Hyun Oh Song

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Deokjae Lee, Seungyong Moon, Junhyeok Lee, Hyun Oh Song

Proceedings of the International Conference on Machine Learning, 2022

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

Proceedings of the International Conference on Machine Learning, 2022

Optimal channel selection with discrete QCQP.

Yeonwoo Jeong, Deokjae Lee, Gaon An, Changyong Son, Hyun Oh Song

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

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

Seungyong Moon, Gaon An, Hyun Oh Song

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble.

Gaon An, Seungyong Moon, Jang-Hyun Kim, Hyun Oh Song

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity.

Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup.

Jang-Hyun Kim, Wonho Choo, Hyun Oh Song

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization.

Seungyong Moon, Gaon An, Hyun Oh Song

Proceedings of the 36th International Conference on Machine Learning, 2019

EMI: Exploration with Mutual Information.

Hyoungseok Kim, Jaekyeom Kim, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Discrete and Continuous Factors of Data via Alternating Disentanglement.

Yeonwoo Jeong, Hyun Oh Song

Proceedings of the 36th International Conference on Machine Learning, 2019

End-To-End Efficient Representation Learning via Cascading Combinatorial Optimization.

Yeonwoo Jeong, Yoonsung Kim, Hyun Oh Song

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

EMI: Exploration with Mutual Information Maximizing State and Action Embeddings.

Hyoungseok Kim, Jaekyeom Kim, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song

CoRR, 2018

Efficient end-to-end learning for quantizable representations.

Yeonwoo Jeong, Hyun Oh Song

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Semantic Instance Segmentation via Deep Metric Learning.

Alireza Fathi, Zbigniew Wojna, Vivek Rathod, Peng Wang, Hyun Oh Song, Sergio Guadarrama, Kevin P. Murphy

CoRR, 2017

Deep Metric Learning via Facility Location.

Hyun Oh Song, Stefanie Jegelka, Vivek Rathod, Kevin Murphy

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Learning to Detect Visual Grasp Affordance.

Hyun Oh Song, Mario Fritz, Daniel Goehring, Trevor Darrell

IEEE Trans Autom. Sci. Eng., 2016

Learnable Structured Clustering Framework for Deep Metric Learning.

Hyun Oh Song, Stefanie Jegelka, Vivek Rathod, Kevin Murphy

CoRR, 2016

Unsupervised Transductive Domain Adaptation.

Ozan Sener, Hyun Oh Song, Ashutosh Saxena, Silvio Savarese

CoRR, 2016

Learning Transferrable Representations for Unsupervised Domain Adaptation.

Ozan Sener, Hyun Oh Song, Ashutosh Saxena, Silvio Savarese

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Deep Metric Learning via Lifted Structured Feature Embedding.

Hyun Oh Song, Yu Xiang, Stefanie Jegelka, Silvio Savarese

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Generalized Sparselet Models for Real-Time Multiclass Object Recognition.

Hyun Oh Song, Ross B. Girshick, Stefan Zickler, Christopher Geyer, Pedro F. Felzenszwalb, Trevor Darrell

IEEE Trans. Pattern Anal. Mach. Intell., 2015

2014

Learning with Parsimony for Large Scale Object Detection and Discovery.

Hyun Oh Song

PhD thesis, 2014

One-Bit Object Detection: On learning to localize objects with minimal supervision.

Hyun Oh Song, Ross B. Girshick, Stefanie Jegelka, Julien Mairal, Zaïd Harchaoui, Trevor Darrell

CoRR, 2014

Weakly-supervised Discovery of Visual Pattern Configurations.

Hyun Oh Song, Yong Jae Lee, Stefanie Jegelka, Trevor Darrell

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On learning to localize objects with minimal supervision.

Hyun Oh Song, Ross B. Girshick, Stefanie Jegelka, Julien Mairal, Zaïd Harchaoui, Trevor Darrell

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Discriminatively Activated Sparselets.

Ross B. Girshick, Hyun Oh Song, Trevor Darrell

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Detection bank: an object detection based video representation for multimedia event recognition.

Tim Althoff, Hyun Oh Song, Trevor Darrell

Proceedings of the 20th ACM Multimedia Conference, MM '12, Nara, Japan, October 29, 2012

Sparselet Models for Efficient Multiclass Object Detection.

Hyun Oh Song, Stefan Zickler, Tim Althoff, Ross B. Girshick, Mario Fritz, Christopher Geyer, Pedro F. Felzenszwalb, Trevor Darrell

Proceedings of the Computer Vision - ECCV 2012, 2012

2011

Visual grasp affordances from appearance-based cues.

Hyun Oh Song, Mario Fritz, Chunhui Gu, Trevor Darrell

Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011