Taesup Moon - RankMe

124 papers A* 27A 7B 3C 1Misc 1Journal 73Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Action-Sufficient Goal Representations. CoRR Jinu Hyeon, Woobin Park, Hongjoon Ahn, Taesup Moon
2026	J	`jnl`	PRISP: Privacy-Safe Few-Shot Personalization via Lightweight Adaptation. CoRR Junho Park, Dohoon Kim, Taesup Moon
2026	J	`jnl`	PopResume: Causal Fairness Evaluation of LLM/VLM Resume Screeners with Population-Representative Dataset. CoRR Sumin Yu, Juhyeon Park, Taesup Moon
2026	J	`jnl`	Uncovering group robustness issue in early diagnosis of MCI to AD conversion and a simple solution: Decoupled classifier with adaptive linear modulation. Biomed. Signal Process. Control. Juhyeon Park, Donggyu Lee, Taesup Moon
2025	J	`jnl`	Cost-Efficient Continual Learning with Sufficient Exemplar Memory. CoRR Dongkyu Cho, Taesup Moon, Rumi Chunara, Kyunghyun Cho, Sungmin Cha
2025	—	`conf`	DoMIX: An Efficient Framework for Exploiting Domain Knowledge in Fine-Tuning. ACL (1) Dohoon Kim, Donghun Kang, Taesup Moon
2025	J	`jnl`	DoMIX: An Efficient Framework for Exploiting Domain Knowledge in Fine-Tuning. CoRR Dohoon Kim, Donghun Kang, Taesup Moon
2025	J	`jnl`	FairDRO: Group fairness regularization via classwise robust optimization. Neural Networks Taeeon Park, Sangwon Jung, Sanghyuk Chun, Taesup Moon
2025	J	`jnl`	Multi-Group Proportional Representation for Text-to-Image Models. CoRR Sangwon Jung, Alex Oesterling, Claudio Mayrink Verdun, Sajani Vithana, Taesup Moon, Flávio P. Calmon
2025	A*	`conf`	Multi-Group Proportional Representations for Text-to-Image Models. CVPR Sangwon Jung, Alex Oesterling, Claudio Mayrink Verdun, Sajani Vithana, Taesup Moon, Flávio P. Calmon
2025	J	`jnl`	Option-aware Temporally Abstracted Value for Offline Goal-Conditioned Reinforcement Learning. CoRR Hongjoon Ahn, Heewoong Choi, Jisu Han, Taesup Moon
2025	J	`jnl`	Physics-Informed Fine-Tuning for physics discovery from random and sparse data. Eng. Appl. Artif. Intell. Yong Jin Jeong, Taesup Moon
2025	A*	`conf`	Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline. ICLR Hongjoon Ahn, Jinu Hyeon, Youngmin Oh, Bosun Hwang, Taesup Moon
2025	J	`jnl`	SEED: Towards More Accurate Semantic Evaluation for Visual Brain Decoding. CoRR Juhyeon Park, Peter Yongho Kim, Jiook Cha, Shinjae Yoo, Taesup Moon
2025	J	`jnl`	SP-Guard: Selective Prompt-adaptive Guidance for Safe Text-to-Image Generation. CoRR Sumin Yu, Taesup Moon
2025	A	`conf`	TLDR: Text Based Last-Layer Retraining for Debiasing Image Classifiers. WACV Juhyeon Park, Seokhyeon Jeong, Taesup Moon
2024	A*	`conf`	Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline. ICLR Donggyu Lee, Sangwon Jung, Taesup Moon
2024	J	`jnl`	Debiased Learning via Composed Conceptual Sensitivity Regularization. IEEE Access Sunghwan Joo, Taesup Moon
2024	A*	`conf`	Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? - A Theoretical and Empirical Study. NeurIPS Sangwon Jung, Sumin Yu, Sanghyuk Chun, Taesup Moon
2024	A*	`conf`	Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers. AAAI Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee
2024	A*	`conf`	Listwise Reward Estimation for Offline Preference-based Reinforcement Learning. ICML Heewoong Choi, Sangwon Jung, Hongjoon Ahn, Taesup Moon
2024	J	`jnl`	Listwise Reward Estimation for Offline Preference-based Reinforcement Learning. CoRR Heewoong Choi, Sangwon Jung, Hongjoon Ahn, Taesup Moon
2024	A*	`conf`	MAFA: Managing False Negatives for Vision-Language Pre-Training. CVPR Jaeseok Byun, Dohoon Kim, Taesup Moon
2024	A	`conf`	NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations. WACV Sungmin Cha, Naeun Ko, Heewoong Choi, Youngjoon Yoo, Taesup Moon
2024	J	`jnl`	Reducing Task Discrepancy of Text Encoders for Zero-Shot Composed Image Retrieval. CoRR Jaeseok Byun, Seokhyeon Jeong, Wonjae Kim, Sanghyuk Chun, Taesup Moon
2024	A*	`conf`	Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning. ICML Sungmin Cha, Kyunghyun Cho, Taesup Moon
2024	J	`jnl`	Reset & Distill: A Recipe for Overcoming Negative Transfer in Continual Reinforcement Learning. CoRR Hongjoon Ahn, Jinu Hyeon, Youngmin Oh, Bosun Hwang, Taesup Moon
2024	—	`conf`	Towards More Diverse Evaluation of Class Incremental Learning: Representation Learning Perspective. CoLLAs Sungmin Cha, Jihwan Kwak, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon
2024	J	`jnl`	Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation. CoRR Jihwan Kwak, Sungmin Cha, Taesup Moon
2024	—	`conf`	Towards realistic incremental scenario in class incremental semantic segmentation. CoLLAs Jihwan Kwak, Sungmin Cha, Taesup Moon
2023	J	`jnl`	Continual Learning in the Presence of Spurious Correlation. CoRR Donggyu Lee, Sangwon Jung, Taesup Moon
2023	J	`jnl`	Converting and Smoothing False Negatives for Vision-Language Pre-training. CoRR Jaeseok Byun, Dohoon Kim, Taesup Moon
2023	—	`conf`	Issues for Continual Learning in the Presence of Dataset Bias. AAAI Bridge Program Donggyu Lee, Sangwon Jung, Taesup Moon
2023	J	`jnl`	Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers. CoRR Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee
2023	J	`jnl`	Observations on K-Image Expansion of Image-Mixing Augmentation. IEEE Access Joonhyun Jeong, Sungmin Cha, Jongwon Choi, Sangdoo Yun, Taesup Moon, Youngjoon Yoo
2023	A*	`conf`	Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization. ICLR Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon
2023	J	`jnl`	Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization. CoRR Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon
2023	A*	`conf`	Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning. CVPR Sungmin Cha, Sungjun Cho, Dasol Hwang, Sunwon Hong, Moontae Lee, Taesup Moon
2023	A*	`conf`	SwiFT: Swin 4D fMRI Transformer. NeurIPS Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, Taesup Moon
2023	J	`jnl`	SwiFT: Swin 4D fMRI Transformer. CoRR Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, Taesup Moon
2023	J	`jnl`	Sy-CON: Symmetric Contrastive Loss for Continual Self-Supervised Representation Learning. CoRR Sungmin Cha, Taesup Moon
2023	J	`jnl`	TLDR: Text Based Last-layer Retraining for Debiasing Image Classifiers. CoRR Juhyeon Park, Seokhyeon Jeong, Taesup Moon
2023	A*	`conf`	Towards More Robust Interpretation via Local Gradient Alignment. AAAI Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon
2022	J	`jnl`	Continual Learning of Micro-Doppler Signature-Based Human Activity Classification. IEEE Geosci. Remote. Sens. Lett. Donggyu Lee, Hyeongmin Park, Taesup Moon, Youngwook Kim
2022	A*	`conf`	Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. NeurIPS Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf
2022	J	`jnl`	Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. CoRR Hongjoon Ahn, Yongyi Yang, Quan Gan, David Wipf, Taesup Moon
2022	J	`jnl`	GAN-Based Framework for Unified Estimation of Process-Induced Random Variation in FinFET. IEEE Access Taeeon Park, Jihwan Kwak, Hongjoon Ahn, Jinwoong Lee, Jaehyuk Lim, Sangho Yu, Changhwan Shin, Taesup Moon
2022	—	`conf`	GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training. ECCV (19) Jaeseok Byun, Taebaek Hwang, Jianlong Fu, Taesup Moon
2022	J	`jnl`	GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training. CoRR Jaeseok Byun, Taebaek Hwang, Jianlong Fu, Taesup Moon
2022	J	`jnl`	Is Continual Learning Truly Learning Representations Continually? CoRR Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon
2022	A*	`conf`	Learning Fair Classifiers with Partially Annotated Group Labels. CVPR Sangwon Jung, Sanghyuk Chun, Taesup Moon
2022	J	`jnl`	Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning. CoRR Sungmin Cha, Soonwon Hong, Moontae Lee, Taesup Moon
2022	J	`jnl`	Towards More Robust Interpretation via Local Gradient Alignment. CoRR Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon
2022	—	`ed.`	xxAI - Beyond Explainable AI - International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers xxAI@ICML Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek
2021	A*	`conf`	CPR: Classifier-Projection Regularization for Continual Learning. ICLR Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flávio P. Calmon, Taesup Moon
2021	J	`jnl`	Deep Learning Aided Blind Synchronization Word Estimation. IEEE Access Yong Sung Kil, Jun Min Song, Sang-Hyo Kim, Taesup Moon, Seok-Ho Chang
2021	A*	`conf`	FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise. CVPR Jaeseok Byun, Sungmin Cha, Taesup Moon
2021	J	`jnl`	FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise. CoRR Jaeseok Byun, Sungmin Cha, Taesup Moon
2021	A*	`conf`	Fair Feature Distillation for Visual Recognition. CVPR Sangwon Jung, Donggyu Lee, Taeeon Park, Taesup Moon
2021	J	`jnl`	Fair Feature Distillation for Visual Recognition. CoRR Sangwon Jung, Donggyu Lee, Taeeon Park, Taesup Moon
2021	A*	`conf`	GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images. ICLR Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon
2021	J	`jnl`	Learning Fair Classifiers with Partially Annotated Group Labels. CoRR Sangwon Jung, Sanghyuk Chun, Taesup Moon
2021	J	`jnl`	Observations on K-image Expansion of Image-Mixing Augmentation for Classification. CoRR Joonhyun Jeong, Sungmin Cha, Youngjoon Yoo, Sangdoo Yun, Taesup Moon, Jongwon Choi
2021	A*	`conf`	SS-IL: Separated Softmax for Incremental Learning. ICCV Hongjoon Ahn, Jihwan Kwak, Subin Lim, Hyeonsu Bang, Hyojun Kim, Taesup Moon
2021	A*	`conf`	SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. NeurIPS Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon
2021	J	`jnl`	SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. CoRR Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon
2021	J	`jnl`	Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack. CoRR Sungmin Cha, Naeun Ko, Youngjoon Yoo, Taesup Moon
2021	J	`jnl`	Supervised Neural Discrete Universal Denoiser for Adaptive Denoising. CoRR Sungmin Cha, Seonwoo Min, Sungroh Yoon, Taesup Moon
2020	J	`jnl`	A Simple Class Decision Balancing for Incremental Learning. CoRR Hongjoon Ahn, Taesup Moon
2020	J	`jnl`	Adaptive Group Sparse Regularization for Continual Learning. CoRR Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon
2020	J	`jnl`	CPR: Classifier-Projection Regularization for Continual Learning. CoRR Sungmin Cha, Hsiang Hsu, Flávio P. Calmon, Taesup Moon
2020	A*	`conf`	Continual Learning with Node-Importance based Adaptive Group Sparse Regularization. NeurIPS Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon
2020	A	`conf`	Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty. UAI Hongjoon Ahn, Taesup Moon
2020	J	`jnl`	Learning Blind Pixelwise Affine Image Denoiser With Single Noisy Images. IEEE Signal Process. Lett. Jaeseok Byun, Taesup Moon
2020	A	`conf`	Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel. AISTATS Taeeon Park, Taesup Moon
2020	J	`jnl`	Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel. CoRR Taeeon Park, Taesup Moon
2020	—	`conf`	xxAI - Beyond Explainable Artificial Intelligence. xxAI@ICML Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek
2019	A*	`conf`	DoPAMINE: Double-Sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling. AAAI Sunghwan Joo, Sungmin Cha, Taesup Moon
2019	J	`jnl`	DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling. CoRR Sunghwan Joo, Sungmin Cha, Taesup Moon
2019	A*	`conf`	Fooling Neural Network Interpretations via Adversarial Model Manipulation. NeurIPS Juyeon Heo, Sunghwan Joo, Taesup Moon
2019	J	`jnl`	Fooling Neural Network Interpretations via Adversarial Model Manipulation. CoRR Juyeon Heo, Sunghwan Joo, Taesup Moon
2019	A*	`conf`	Fully Convolutional Pixel Adaptive Image Denoiser. ICCV Sungmin Cha, Taesup Moon
2019	J	`jnl`	GAN2GAN: Generative Noise Learning for Blind Image Denoising with Single Noisy Images. CoRR Sungmin Cha, Taeeon Park, Taesup Moon
2019	J	`jnl`	Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty. CoRR Hongjoon Ahn, Taesup Moon
2019	J	`jnl`	Skip-connected 3D DenseNet for volumetric infant brain MRI segmentation. Biomed. Signal Process. Control. Toan Duc Bui, Jitae Shin, Taesup Moon
2019	A*	`conf`	Subtask Gated Networks for Non-Intrusive Load Monitoring. AAAI Changho Shin, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, Wonjong Rhee
2019	A*	`conf`	Uncertainty-based Continual Learning with Adaptive Regularization. NeurIPS Hongjoon Ahn, Sungmin Cha, Donggyu Lee, Taesup Moon
2019	J	`jnl`	Uncertainty-based Continual Learning with Adaptive Regularization. CoRR Hongjoon Ahn, Donggyu Lee, Sungmin Cha, Taesup Moon
2019	—	`conf`	Working Vacation Scheduling of M RiTA Yongbee Park, Taesup Moon
2018	J	`jnl`	Fully Convolutional Pixel Adaptive Image Denoiser. CoRR Sungmin Cha, Taesup Moon
2018	Misc	`conf`	Neural Adaptive Image Denoiser. ICASSP Sungmin Cha, Taesup Moon
2018	J	`jnl`	Subtask Gated Networks for Non-Intrusive Load Monitoring. CoRR Changho Shin, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, Wonjong Rhee
2018	—	`conf`	UDLR Convolutional Network for Adaptive Image Denoiser. RiTA Sungmin Cha, Taesup Moon
2017	J	`jnl`	3D Densely Convolutional Networks for Volumetric Segmentation. CoRR Toan Duc Bui, Jitae Shin, Taesup Moon
2017	J	`jnl`	Neural Affine Grayscale Image Denoising. CoRR Sungmin Cha, Taesup Moon
2017	J	`jnl`	Uniform Concentration of the Loss Estimator for Neural DUDE. CoRR Taesup Moon
2016	J	`jnl`	Human Detection and Activity Classification Based on Micro-Doppler Signatures Using Deep Convolutional Neural Networks. IEEE Geosci. Remote. Sens. Lett. Youngwook Kim, Taesup Moon
2016	J	`jnl`	Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks. Sensors Jinhee Park, Rios Jesus Javier, Taesup Moon, Youngwook Kim
2016	—	`conf`	Neural Universal Discrete Denoiser. NIPS Taesup Moon, Seonwoo Min, Byunghan Lee, Sungroh Yoon
2016	J	`jnl`	Neural Universal Discrete Denoiser. CoRR Taesup Moon, Seonwoo Min
2016	J	`jnl`	Regularization and Kernelization of the Maximin Correlation Approach. IEEE Access Taehoon Lee, Taesup Moon, Seung Jean Kim, Sungroh Yoon
2015	J	`jnl`	DUDE-Seq: Fast Universal Denoising of Nucleotide Sequences. CoRR Byunghan Lee, Taesup Moon, Sungroh Yoon, Tsachy Weissman
2015	J	`jnl`	Evaluation of a MISR-Based High-Resolution Aerosol Retrieval Method Using AERONET DRAGON Campaign Data. IEEE Trans. Geosci. Remote. Sens. Taesup Moon, Yueqing Wang, Yang Liu, Bin Yu
2015	C	`conf`	RNNDROP: A novel dropout for RNNS in ASR. ASRU Taesup Moon, Heeyoul Choi, Hoshik Lee, Inchul Song
2015	J	`jnl`	Regularization and Kernelization of the Maximin Correlation Approach. CoRR Taehoon Lee, Taesup Moon, Seung Jean Kim, Sungroh Yoon
2014	J	`jnl`	Exploiting User Preference for Online Learning in Web Content Optimization Systems. ACM Trans. Intell. Syst. Technol. Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, Yi Chang
2012	J	`jnl`	An Online Learning Framework for Refining Recency Search Results with User Click Feedback. ACM Trans. Inf. Syst. Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang
2012	—	`conf`	Bandits with Generalized Linear Models. ICML On-line Trading of Exploration and Exploitation Lihong Li, Wei Chu, John Langford, Taesup Moon, Xuanhui Wang
2012	J	`jnl`	Universal Switching FIR Filtering. IEEE Trans. Signal Process. Taesup Moon
2011	B	`conf`	Discrete denoising of heterogeneous two-dimensional data. ISIT Taesup Moon, Tsachy Weissman, Jae-Young Kim
2011	A*	`conf`	Learning to model relatedness for news recommendation. WWW Yuanhua Lv, Taesup Moon, Pranam Kolari, Zhaohui Zheng, Xuanhui Wang, Yi Chang
2011	J	`jnl`	Refining Recency Search Results with User Click Feedback CoRR Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang
2010	J	`jnl`	Discrete denoising of heterogenous two-dimensional data CoRR Taesup Moon, Tsachy Weissman, Jae-Young Kim
2010	A	`conf`	IntervalRank: isotonic regression with listwise and pairwise constraints. WSDM Taesup Moon, Alexander J. Smola, Yi Chang, Zhaohui Zheng
2010	A	`conf`	Online learning for recency search ranking using real-time user feedback. CIKM Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohui Zheng, Yi Chang
2010	A	`conf`	User behavior driven ranking without editorial judgments. CIKM Taesup Moon, Georges Dupret, Shihao Ji, Ciya Liao, Zhaohui Zheng
2009	J	`jnl`	Discrete denoising with shifts. IEEE Trans. Inf. Theory Taesup Moon, Tsachy Weissman
2009	J	`jnl`	Universal FIR MMSE Filtering. IEEE Trans. Signal Process. Taesup Moon, Tsachy Weissman
2008	J	`jnl`	Universal Filtering Via Hidden Markov Modeling. IEEE Trans. Inf. Theory Taesup Moon, Tsachy Weissman
2007	B	`conf`	Competitive On-line Linear FIR MMSE Filtering. ISIT Taesup Moon, Tsachy Weissman
2007	J	`jnl`	Discrete Denoising with Shifts CoRR Taesup Moon, Tsachy Weissman
2006	—	`conf`	Soft Sensor Using PNN Model and Rule Base for Wastewater Treatment Plant. ISNN (2) Yejin Kim, Hyeon Bae, Kyungmin Poo, Jongrack Kim, Taesup Moon, Sungshin Kim, Changwon Kim
2006	J	`jnl`	Universal Filtering via Hidden Markov Modeling CoRR Taesup Moon, Tsachy Weissman
2005	B	`conf`	Discrete universal filtering via hidden Markov modelling. ISIT Taesup Moon, Tsachy Weissman