Visual grasp affordances from appearance-based cues. - Hyun Oh Song; Mario Fritz; Chunhui Gu; Trevor Darrell (ICCV Workshops, 2011)

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 (ECCV (2), 2012)

Detection bank: an object detection based video representation for multimedia event recognition. - Tim Althoff; Hyun Oh Song; Trevor Darrell (ACM Multimedia, 2012)

Discriminatively Activated Sparselets. - Ross B. Girshick; Hyun Oh Song; Trevor Darrell (ICML (1), 2013)

On learning to localize objects with minimal supervision. - Hyun Oh Song; Ross B. Girshick; Stefanie Jegelka; Julien Mairal; Zaïd Harchaoui; Trevor Darrell (ICML, 2014)

Weakly-supervised Discovery of Visual Pattern Configurations. - Hyun Oh Song; Yong Jae Lee; Stefanie Jegelka; Trevor Darrell (NIPS, 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)

Learning with Parsimony for Large Scale Object Detection and Discovery. - Hyun Oh Song (2014)

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)

Deep Metric Learning via Lifted Structured Feature Embedding. - Hyun Oh Song; Yu Xiang; Stefanie Jegelka; Silvio Savarese (CVPR, 2016)

Learning Transferrable Representations for Unsupervised Domain Adaptation. - Ozan Sener; Hyun Oh Song; Ashutosh Saxena; Silvio Savarese (NIPS, 2016)

Unsupervised Transductive Domain Adaptation. - Ozan Sener; Hyun Oh Song; Ashutosh Saxena; Silvio Savarese (CoRR, 2016)

Learnable Structured Clustering Framework for Deep Metric Learning. - Hyun Oh Song; Stefanie Jegelka; Vivek Rathod; Kevin Murphy 002 (CoRR, 2016)

Learning to Detect Visual Grasp Affordance. - Hyun Oh Song; Mario Fritz; Daniel Goehring; Trevor Darrell (IEEE Trans Autom. Sci. Eng., 2016)

Deep Metric Learning via Facility Location. - Hyun Oh Song; Stefanie Jegelka; Vivek Rathod; Kevin Murphy 002 (CVPR, 2017)

Semantic Instance Segmentation via Deep Metric Learning. - Alireza Fathi; Zbigniew Wojna; Vivek Rathod; Peng Wang 001; Hyun Oh Song; Sergio Guadarrama; Kevin P. Murphy (CoRR, 2017)

Efficient end-to-end learning for quantizable representations. - Yeonwoo Jeong; Hyun Oh Song (ICML, 2018)

EMI: Exploration with Mutual Information Maximizing State and Action Embeddings. - Hyoungseok Kim; Jaekyeom Kim; Yeonwoo Jeong; Sergey Levine; Hyun Oh Song (CoRR, 2018)

End-To-End Efficient Representation Learning via Cascading Combinatorial Optimization. - Yeonwoo Jeong; Yoonsung Kim; Hyun Oh Song (CVPR, 2019)

Learning Discrete and Continuous Factors of Data via Alternating Disentanglement. - Yeonwoo Jeong; Hyun Oh Song (ICML, 2019)

EMI: Exploration with Mutual Information. - Hyoungseok Kim; Jaekyeom Kim; Yeonwoo Jeong; Sergey Levine; Hyun Oh Song (ICML, 2019)

Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization. - Seungyong Moon; Gaon An; Hyun Oh Song (ICML, 2019)

Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup. - Jang-Hyun Kim; Wonho Choo; Hyun Oh Song (ICML, 2020)

Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity. - Jang-Hyun Kim; Wonho Choo; Hosan Jeong; Hyun Oh Song (ICLR, 2021)

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble. - Gaon An; Seungyong Moon; Jang-Hyun Kim; Hyun Oh Song (NeurIPS, 2021)

Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks. - Seungyong Moon; Gaon An; Hyun Oh Song (AAAI, 2022)

Optimal channel selection with discrete QCQP. - Yeonwoo Jeong; Deokjae Lee; Gaon An; Changyong Son; Hyun Oh Song (AISTATS, 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 001; Hyun Oh Song (ICML, 2022)

Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization. - Deokjae Lee; Seungyong Moon; Junhyeok Lee 004; Hyun Oh Song (ICML, 2022)

Rethinking Value Function Learning for Generalization in Reinforcement Learning. - Seungyong Moon; JunYeong Lee; Hyun Oh Song (NeurIPS, 2022)

Query-Efficient Black-Box Red Teaming via Bayesian Optimization. - Deokjae Lee; JunYeong Lee; Jung-Woo Ha 001; Jin-Hwa Kim; Sang-Woo Lee 001; Hwaran Lee; Hyun Oh Song (ACL (1), 2023)

Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming. - Jinuk Kim; Yeonwoo Jeong; Deokjae Lee; Hyun Oh Song (ICML, 2023)

Direct Preference-based Policy Optimization without Reward Modeling. - Gaon An; Junhyeok Lee 004; Xingdong Zuo; Norio Kosaka; Kyung-Min Kim; Hyun Oh Song (NeurIPS, 2023)

Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data. - Jang-Hyun Kim; Sangdoo Yun; Hyun Oh Song (NeurIPS, 2023)

Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning. - Seungyong Moon; Junyoung Yeom; Bumsoo Park; Hyun Oh Song (NeurIPS, 2023)

Neural Relation Graph for Identifying Problematic Data. - Jang-Hyun Kim; Sangdoo Yun; Hyun Oh Song (CoRR, 2023)

Designing an offline reinforcement learning objective from scratch. - Gaon An; Junhyeok Lee 004; Xingdong Zuo; Norio Kosaka; Kyung-Min Kim; Hyun Oh Song (CoRR, 2023)

Compressed Context Memory for Online Language Model Interaction. - Jang-Hyun Kim; Junyoung Yeom; Sangdoo Yun; Hyun Oh Song (ICLR, 2024)

LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging. - Jinuk Kim; Marwa El Halabi; Mingi Ji; Hyun Oh Song (ICML, 2024)

Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization. - Deokjae Lee; Hyun Oh Song; Kyunghyun Cho (ICML, 2024)

Targeted Cause Discovery with Data-Driven Learning. - Jang-Hyun Kim; Claudia Skok Gibbs; Sangdoo Yun; Hyun Oh Song; Kyunghyun Cho (CoRR, 2024)

Guided Stream of Search: Learning to Better Search with Language Models via Optimal Path Guidance. - Seungyong Moon; Bumsoo Park; Hyun Oh Song (CoRR, 2024)

GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance. - Jinuk Kim; Marwa El Halabi; Wonpyo Park; Clemens JS Schaefer; Deokjae Lee; Yeonhong Park; Jae W. Lee; Hyun Oh Song (CoRR, 2025)

KVzip: Query-Agnostic KV Cache Compression with Context Reconstruction. - Jang-Hyun Kim; Jinuk Kim; Sangwoo Kwon; Jae W. Lee; Sangdoo Yun; Hyun Oh Song (CoRR, 2025)