Kyungwoo Song

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 58

Top Topics

Approximate Inference

Recurrent Neural Networks

Top Venues

Publications

Jeyoon Yeom, Taero Kim, Rakwoo Chang, Kyungwoo Song
Structural and positional ensembled encoding for Graph Transformer. Pattern Recognit. Lett. 183 (2024)
Jeyoon Yeom, Hakyung Lee, Hoyoon Byun, Yewon Kim, Jeongeun Byun, Yunjeong Choi, Sungjin Kim, Kyungwoo Song
Tc-llama 2: fine-tuning LLM for technology and commercialization applications. J. Big Data 11 (1) (2024)
Sungjun Lim, Jeyoon Yeom, Sooyon Kim, Hoyoon Byun, Jinho Kang, Yohan Jung, Jiyoung Jung, Kyungwoo Song
Flat Posterior Does Matter For Bayesian Transfer Learning. CoRR (2024)
Haeji Jung, Changdae Oh, Jooeon Kang, Jimin Sohn, Kyungwoo Song, Jinkyu Kim, David R. Mortensen
Mitigating the Linguistic Gap with Phonemic Representations for Robust Multilingual Language Understanding. CoRR (2024)
Changdae Oh, Gyeongdeok Seo, Geunyoung Jung, Zhi-Qi Cheng, Hosik Choi, Jiyoung Jung, Kyungwoo Song
Robust Adaptation of Foundation Models with Black-Box Visual Prompting. CoRR (2024)
Keon-Hee Park, Kyungwoo Song, Gyeong-Moon Park
Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners. CoRR (2024)
Changdae Oh, Minhoi Park, Sungjun Lim, Kyungwoo Song
Language model-guided student performance prediction with multimodal auxiliary information. Expert Syst. Appl. 250 (2024)
Jinho Kang, Taero Kim, Yewon Kim, Changdae Oh, Jiyoung Jung, Rakwoo Chang, Kyungwoo Song
Bibimbap : Pre-trained models ensemble for Domain Generalization. Pattern Recognit. 151 (2024)
SeungHwan An, Kyungwoo Song, Jong-June Jeon
Causally Disentangled Generative Variational AutoEncoder. ECAI (2023)
Dongjun Kim, Kyungwoo Song, Yoon-Yeong Kim, Yongjin Shin, Wanmo Kang, Il-Chul Moon, Weonyoung Joo
Sequential Likelihood-Free Inference with Neural Proposal. Pattern Recognit. Lett. 169 (2023)
Hyeondey Kim, Jinwoo Nam, Minjae Lee, Yun Jegal, Kyungwoo Song
Leveraging Skill-to-Skill Supervision for Knowledge Tracing. CoRR (2023)
Yewon Kim, YongTaek Lim, Dokyung Yoon, Kyungwoo Song
RPLKG: Robust Prompt Learning with Knowledge Graph. CoRR (2023)
Changdae Oh, Junhyuk So, Hoyoon Byun, YongTaek Lim, Minchul Shin, Jong-June Jeon, Kyungwoo Song
Geodesic Multi-Modal Mixup for Robust Fine-Tuning. NeurIPS (2023)
SeungHwan An, Kyungwoo Song, Jong-June Jeon
Causally Disentangled Generative Variational AutoEncoder. CoRR (2023)
Changdae Oh, Hyeji Hwang, Hee Young Lee, YongTaek Lim, Geunyoung Jung, Jiyoung Jung, Hosik Choi, Kyungwoo Song
BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning. CVPR (2023)
Changdae Oh, Hyeji Hwang, Hee Young Lee, YongTaek Lim, Geunyoung Jung, Jiyoung Jung, Hosik Choi, Kyungwoo Song
BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning. CoRR (2023)
Changdae Oh, Mijoo Kim, Hyesu Lim, Junhyeok Park, Euiseog Jeong, Zhi-Qi Cheng, Kyungwoo Song
Towards Calibrated Robust Fine-Tuning of Vision-Language Models. CoRR (2023)
Junhyuk So, YongTaek Lim, Yewon Kim, Changdae Oh, Kyungwoo Song
Robust Contrastive Learning With Dynamic Mixed Margin. IEEE Access 11 (2023)
Yoon-Yeong Kim, Youngjae Cho, JoonHo Jang, Byeonghu Na, Yeongmin Kim, Kyungwoo Song, Wanmo Kang, Il-Chul Moon
SAAL: Sharpness-Aware Active Learning. ICML (2023)
Taero Kim, Sungjun Lim, Kyungwoo Song
Sharpness-aware Minimization for Worst Case Optimization. CoRR (2022)
Changdae Oh, Heeji Won, Junhyuk So, Taero Kim, Yewon Kim, Hosik Choi, Kyungwoo Song
Learning Fair Representation via Distributional Contrastive Disentanglement. KDD (2022)
HeeSun Bae, Seungjae Shin, Byeonghu Na, JoonHo Jang, Kyungwoo Song, Il-Chul Moon
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model. ICML (2022)
HeeSun Bae, Seungjae Shin, Byeonghu Na, JoonHo Jang, Kyungwoo Song, Il-Chul Moon
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model. CoRR (2022)
Changdae Oh, Heeji Won, Junhyuk So, Taero Kim, Yewon Kim, Hosik Choi, Kyungwoo Song
Learning Fair Representation via Distributional Contrastive Disentanglement. CoRR (2022)
Seyun Bae, Hoyoon Byun, Changdae Oh, Yoon-Sik Cho, Kyungwoo Song
Graph Perceiver IO: A General Architecture for Graph Structured Data. CoRR (2022)
Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-Chul Moon
Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation. ICML (2022)
JoonHo Jang, Byeonghu Na, DongHyeok Shin, Mingi Ji, Kyungwoo Song, Il-Chul Moon
Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation. CoRR (2022)
Yohan Jung, Kyungwoo Song, Jinkyoo Park
Efficient Approximate Inference for Stationary Kernel on Frequency Domain. ICML (2022)
JoonHo Jang, Byeonghu Na, DongHyeok Shin, Mingi Ji, Kyungwoo Song, Il-Chul Moon
Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation. NeurIPS (2022)
Junhyuk So, Changdae Oh, Minchul Shin, Kyungwoo Song
Multi-Modal Mixup for Robust Fine-tuning. CoRR (2022)
Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-Chul Moon
Score Matching Model for Unbounded Data Score. CoRR (2021)
Yoon-Yeong Kim, Kyungwoo Song, JoonHo Jang, Il-Chul Moon
LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning. NeurIPS (2021)
Dongjun Kim, Kyungwoo Song, Seungjae Shin, Wanmo Kang, Il-Chul Moon
Posterior-Aided Regularization for Likelihood-Free Inference. CoRR (2021)
Kyungwoo Song, Yohan Jung, Dongjun Kim, Il-Chul Moon
Implicit Kernel Attention. AAAI (2021)
Hyemi Kim, Seungjae Shin, JoonHo Jang, Kyungwoo Song, Weonyoung Joo, Wanmo Kang, Il-Chul Moon
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder. AAAI (2021)
Byeonghu Na, Hyemi Kim, Kyungwoo Song, Weonyoung Joo, Yoon-Yeong Kim, Il-Chul Moon
Deep Generative Positive-Unlabeled Learning under Selection Bias. CIKM (2020)
Kyungwoo Song, JoonHo Jang, Seungjae Shin, Il-Chul Moon
Bivariate Beta-LSTM. AAAI (2020)
Seungjae Shin, Kyungwoo Song, JoonHo Jang, Hyemi Kim, Weonyoung Joo, Il-Chul Moon
Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation. EMNLP (Findings) (2020)
Seungjae Shin, Kyungwoo Song, JoonHo Jang, Hyemi Kim, Weonyoung Joo, Il-Chul Moon
Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation. CoRR (2020)
Mingi Ji, Weonyoung Joo, Kyungwoo Song, Yoon-Yeong Kim, Il-Chul Moon
Sequential Recommendation with Relation-Aware Kernelized Self-Attention. AAAI (2020)
Yoon-Yeong Kim, Kyungwoo Song, JoonHo Jang, Il-Chul Moon
LADA: Look-Ahead Data Acquisition via Augmentation for Active Learning. CoRR (2020)
Dongjun Kim, Kyungwoo Song, Yoon-Yeong Kim, Yongjin Shin, Il-Chul Moon
Sequential Likelihood-Free Inference with Implicit Surrogate Proposal. CoRR (2020)
Yohan Jung, Kyungwoo Song, Jinkyoo Park
Approximate Inference for Spectral Mixture Kernel. CoRR (2020)
Su-Jin Shin, Kyungwoo Song, Il-Chul Moon
Hierarchically Clustered Representation Learning. AAAI (2020)
Kyungwoo Song, Yohan Jung, Dongjun Kim, Il-Chul Moon
Implicit Kernel Attention. CoRR (2020)
Kyungwoo Song
Context Aware Sequence Modeling. IJCAI (2020)
Hyemi Kim, Seungjae Shin, JoonHo Jang, Kyungwoo Song, Weonyoung Joo, Wanmo Kang, Il-Chul Moon
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder. CoRR (2020)
Mingi Ji, Weonyoung Joo, Kyungwoo Song, Yoon-Yeong Kim, Il-Chul Moon
Sequential Recommendation with Relation-Aware Kernelized Self-Attention. CoRR (2019)
Kyungwoo Song, JoonHo Jang, Seungjae Shin, Il-Chul Moon
Bivariate Beta LSTM. CoRR (2019)
Su-Jin Shin, Kyungwoo Song, Il-Chul Moon
Hierarchically Clustered Representation Learning. CoRR (2019)
Sungrae Park, Kyungwoo Song, Mingi Ji, Wonsung Lee, Il-Chul Moon
Adversarial Dropout for Recurrent Neural Networks. AAAI (2019)
Kyungwoo Song, Mingi Ji, Sungrae Park, Il-Chul Moon
Hierarchical Context enabled Recurrent Neural Network for Recommendation. CoRR (2019)
Kyungwoo Song, Mingi Ji, Sungrae Park, Il-Chul Moon
Hierarchical Context Enabled Recurrent Neural Network for Recommendation. AAAI (2019)
Sungrae Park, Kyungwoo Song, Mingi Ji, Wonsung Lee, Il-Chul Moon
Adversarial Dropout for Recurrent Neural Networks. CoRR (2019)
Kyungwoo Song, Wonsung Lee, Il-Chul Moon
Neural Ideal Point Estimation Network. CoRR (2019)
Kyungwoo Song, Wonsung Lee, Il-Chul Moon
Neural Ideal Point Estimation Network. AAAI (2018)
Wonsung Lee, Kyungwoo Song, Il-Chul Moon
Augmented Variational Autoencoders for Collaborative Filtering with Auxiliary Information. CIKM (2017)
Kyungwoo Song, Sang-Hyeon Kim, Jinhyung Tak, Han-Lim Choi, Il-Chul Moon
Data-driven ballistic coefficient learning for future state prediction of high-speed vehicles. FUSION (2016)
Kyungwoo Song, Qin Wang, Yuxi Zheng
The Regularity of Semihyperbolic Patches Near Sonic Lines for The 2-D Euler System in Gas Dynamics. SIAM J. Math. Anal. 47 (3) (2015)
Kyungwoo Song, Do-Hyeong Kim, Su-Jin Shin, Il-Chul Moon
Identifying the evolution of disasters and responses with network-text analysis. SMC (2014)