Taesup Moon

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 76

Top Topics

Incremental Learning

Top Venues

Publications

Jaeseok Byun, Seokhyeon Jeong, Wonjae Kim, Sanghyuk Chun, Taesup Moon
Reducing Task Discrepancy of Text Encoders for Zero-Shot Composed Image Retrieval. CoRR (2024)
Donggyu Lee, Sangwon Jung, Taesup Moon
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline. ICLR (2024)
Sungmin Cha, Naeun Ko, Heewoong Choi, Youngjoon Yoo, Taesup Moon
NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations. WACV (2024)
Jihwan Kwak, Sungmin Cha, Taesup Moon
Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation. CoRR (2024)
Hongjoon Ahn, Jinu Hyeon, Youngmin Oh, Bosun Hwang, Taesup Moon
Reset & Distill: A Recipe for Overcoming Negative Transfer in Continual Reinforcement Learning. CoRR (2024)
Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee
Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers. AAAI (2024)
Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization. CoRR (2023)
Donggyu Lee, Sangwon Jung, Taesup Moon
Issues for Continual Learning in the Presence of Dataset Bias. AAAI Bridge Program (2023)
Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, Taesup Moon
SwiFT: Swin 4D fMRI Transformer. CoRR (2023)
Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, Taesup Moon
SwiFT: Swin 4D fMRI Transformer. NeurIPS (2023)
Juhyeon Park, Seokhyeon Jeong, Taesup Moon
TLDR: Text Based Last-layer Retraining for Debiasing Image Classifiers. CoRR (2023)
Donggyu Lee, Sangwon Jung, Taesup Moon
Continual Learning in the Presence of Spurious Correlation. CoRR (2023)
Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon
Towards More Robust Interpretation via Local Gradient Alignment. AAAI (2023)
Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers. CoRR (2023)
Jaeseok Byun, Dohoon Kim, Taesup Moon
Converting and Smoothing False Negatives for Vision-Language Pre-training. CoRR (2023)
Sungmin Cha, Taesup Moon
Sy-CON: Symmetric Contrastive Loss for Continual Self-Supervised Representation Learning. CoRR (2023)
Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization. ICLR (2023)
Sungmin Cha, Sungjun Cho, Dasol Hwang, Sunwon Hong, Moontae Lee, Taesup Moon
Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning. CVPR (2023)
Joonhyun Jeong, Sungmin Cha, Jongwon Choi, Sangdoo Yun, Taesup Moon, Youngjoon Yoo
Observations on K-Image Expansion of Image-Mixing Augmentation. IEEE Access 11 (2023)
Taeeon Park, Jihwan Kwak, Hongjoon Ahn, Jinwoong Lee, Jaehyuk Lim, Sangho Yu, Changhwan Shin, Taesup Moon
GAN-Based Framework for Unified Estimation of Process-Induced Random Variation in FinFET. IEEE Access 10 (2022)
Jaeseok Byun, Taebaek Hwang, Jianlong Fu, Taesup Moon
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training. ECCV (19) (2022)
Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. NeurIPS (2022)
Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon
Is Continual Learning Truly Learning Representations Continually? CoRR (2022)
Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon
Towards More Robust Interpretation via Local Gradient Alignment. CoRR (2022)
Donggyu Lee, Hyeongmin Park, Taesup Moon, Youngwook Kim
Continual Learning of Micro-Doppler Signature-Based Human Activity Classification. IEEE Geosci. Remote. Sens. Lett. 19 (2022)
Hongjoon Ahn, Yongyi Yang, Quan Gan, David Wipf, Taesup Moon
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. CoRR (2022)
Sangwon Jung, Sanghyuk Chun, Taesup Moon
Learning Fair Classifiers with Partially Annotated Group Labels. CVPR (2022)
Sungmin Cha, Soonwon Hong, Moontae Lee, Taesup Moon
Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning. CoRR (2022)
Jaeseok Byun, Taebaek Hwang, Jianlong Fu, Taesup Moon
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training. CoRR (2022)
Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. NeurIPS (2021)
Yong Sung Kil, Jun Min Song, Sang-Hyo Kim, Taesup Moon, Seok-Ho Chang
Deep Learning Aided Blind Synchronization Word Estimation. IEEE Access 9 (2021)
Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flávio P. Calmon, Taesup Moon
CPR: Classifier-Projection Regularization for Continual Learning. ICLR (2021)
Jaeseok Byun, Sungmin Cha, Taesup Moon
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise. CVPR (2021)
Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon
GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images. ICLR (2021)
Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. CoRR (2021)
Sangwon Jung, Donggyu Lee, Taeeon Park, Taesup Moon
Fair Feature Distillation for Visual Recognition. CVPR (2021)
Joonhyun Jeong, Sungmin Cha, Youngjoon Yoo, Sangdoo Yun, Taesup Moon, Jongwon Choi
Observations on K-image Expansion of Image-Mixing Augmentation for Classification. CoRR (2021)
Sangwon Jung, Sanghyuk Chun, Taesup Moon
Learning Fair Classifiers with Partially Annotated Group Labels. CoRR (2021)
Jaeseok Byun, Sungmin Cha, Taesup Moon
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise. CoRR (2021)
Sungmin Cha, Naeun Ko, Youngjoon Yoo, Taesup Moon
Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack. CoRR (2021)
Hongjoon Ahn, Jihwan Kwak, Subin Lim, Hyeonsu Bang, Hyojun Kim, Taesup Moon
SS-IL: Separated Softmax for Incremental Learning. ICCV (2021)
Sungmin Cha, Seonwoo Min, Sungroh Yoon, Taesup Moon
Supervised Neural Discrete Universal Denoiser for Adaptive Denoising. CoRR (2021)
Sangwon Jung, Donggyu Lee, Taeeon Park, Taesup Moon
Fair Feature Distillation for Visual Recognition. CoRR (2021)
Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon
Continual Learning with Node-Importance based Adaptive Group Sparse Regularization. NeurIPS (2020)
Taeeon Park, Taesup Moon
Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel. CoRR (2020)
Hongjoon Ahn, Taesup Moon
A Simple Class Decision Balancing for Incremental Learning. CoRR (2020)
Jaeseok Byun, Taesup Moon
Learning Blind Pixelwise Affine Image Denoiser With Single Noisy Images. IEEE Signal Process. Lett. 27 (2020)
Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek
xxAI - Beyond Explainable Artificial Intelligence. xxAI@ICML (2020)
Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon
Adaptive Group Sparse Regularization for Continual Learning. CoRR (2020)
Hongjoon Ahn, Taesup Moon
Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty. UAI (2020)
Sungmin Cha, Hsiang Hsu, Flávio P. Calmon, Taesup Moon
CPR: Classifier-Projection Regularization for Continual Learning. CoRR (2020)
Taeeon Park, Taesup Moon
Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel. AISTATS (2020)
Hongjoon Ahn, Taesup Moon
Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty. CoRR (2019)
Hongjoon Ahn, Donggyu Lee, Sungmin Cha, Taesup Moon
Uncertainty-based Continual Learning with Adaptive Regularization. CoRR (2019)
Sunghwan Joo, Sungmin Cha, Taesup Moon
DoPAMINE: Double-Sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling. AAAI (2019)
Juyeon Heo, Sunghwan Joo, Taesup Moon
Fooling Neural Network Interpretations via Adversarial Model Manipulation. NeurIPS (2019)
Sungmin Cha, Taesup Moon
Fully Convolutional Pixel Adaptive Image Denoiser. ICCV (2019)
Sungmin Cha, Taeeon Park, Taesup Moon
GAN2GAN: Generative Noise Learning for Blind Image Denoising with Single Noisy Images. CoRR (2019)
Sunghwan Joo, Sungmin Cha, Taesup Moon
DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling. CoRR (2019)
Yongbee Park, Taesup Moon
/M/1/N System using Neural Network. RiTA (2019)
Toan Duc Bui, Jitae Shin, Taesup Moon
Skip-connected 3D DenseNet for volumetric infant brain MRI segmentation. Biomed. Signal Process. Control. 54 (2019)
Hongjoon Ahn, Sungmin Cha, Donggyu Lee, Taesup Moon
Uncertainty-based Continual Learning with Adaptive Regularization. NeurIPS (2019)
Changho Shin, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, Wonjong Rhee
Subtask Gated Networks for Non-Intrusive Load Monitoring. AAAI (2019)
Juyeon Heo, Sunghwan Joo, Taesup Moon
Fooling Neural Network Interpretations via Adversarial Model Manipulation. CoRR (2019)
Sungmin Cha, Taesup Moon
Fully Convolutional Pixel Adaptive Image Denoiser. CoRR (2018)
Changho Shin, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, Wonjong Rhee
Subtask Gated Networks for Non-Intrusive Load Monitoring. CoRR (2018)
Sungmin Cha, Taesup Moon
UDLR Convolutional Network for Adaptive Image Denoiser. RiTA (2018)
Sungmin Cha, Taesup Moon
Neural Adaptive Image Denoiser. ICASSP (2018)
Sungmin Cha, Taesup Moon
Neural Affine Grayscale Image Denoising. CoRR (2017)
Taesup Moon
Uniform Concentration of the Loss Estimator for Neural DUDE. CoRR (2017)
Toan Duc Bui, Jitae Shin, Taesup Moon
3D Densely Convolutional Networks for Volumetric Segmentation. CoRR (2017)
Taehoon Lee, Taesup Moon, Seung Jean Kim, Sungroh Yoon
Regularization and Kernelization of the Maximin Correlation Approach. IEEE Access 4 (2016)
Taesup Moon, Seonwoo Min, Byunghan Lee, Sungroh Yoon
Neural Universal Discrete Denoiser. NIPS (2016)
Jinhee Park, Rios Jesus Javier, Taesup Moon, Youngwook Kim
Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks. Sensors 16 (12) (2016)
Taesup Moon, Seonwoo Min
Neural Universal Discrete Denoiser. CoRR (2016)
Youngwook Kim, Taesup Moon
Human Detection and Activity Classification Based on Micro-Doppler Signatures Using Deep Convolutional Neural Networks. IEEE Geosci. Remote. Sens. Lett. 13 (1) (2016)
Byunghan Lee, Taesup Moon, Sungroh Yoon, Tsachy Weissman
DUDE-Seq: Fast Universal Denoising of Nucleotide Sequences. CoRR (2015)
Taehoon Lee, Taesup Moon, Seung Jean Kim, Sungroh Yoon
Regularization and Kernelization of the Maximin Correlation Approach. CoRR (2015)
Taesup Moon, Heeyoul Choi, Hoshik Lee, Inchul Song
RNNDROP: A novel dropout for RNNS in ASR. ASRU (2015)
Taesup Moon, Yueqing Wang, Yang Liu, Bin Yu
Evaluation of a MISR-Based High-Resolution Aerosol Retrieval Method Using AERONET DRAGON Campaign Data. IEEE Trans. Geosci. Remote. Sens. 53 (8) (2015)
Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, Yi Chang
Exploiting User Preference for Online Learning in Web Content Optimization Systems. ACM Trans. Intell. Syst. Technol. 5 (2) (2014)
Taesup Moon
Universal Switching FIR Filtering. IEEE Trans. Signal Process. 60 (3) (2012)
Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang
An Online Learning Framework for Refining Recency Search Results with User Click Feedback. ACM Trans. Inf. Syst. 30 (4) (2012)
Lihong Li, Wei Chu, John Langford, Taesup Moon, Xuanhui Wang
Bandits with Generalized Linear Models. ICML On-line Trading of Exploration and Exploitation (2012)
Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang
Refining Recency Search Results with User Click Feedback CoRR (2011)
Taesup Moon, Tsachy Weissman, Jae-Young Kim
Discrete denoising of heterogeneous two-dimensional data. ISIT (2011)
Yuanhua Lv, Taesup Moon, Pranam Kolari, Zhaohui Zheng, Xuanhui Wang, Yi Chang
Learning to model relatedness for news recommendation. WWW (2011)
Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohui Zheng, Yi Chang
Online learning for recency search ranking using real-time user feedback. CIKM (2010)
Taesup Moon, Tsachy Weissman, Jae-Young Kim
Discrete denoising of heterogenous two-dimensional data CoRR (2010)
Taesup Moon, Georges Dupret, Shihao Ji, Ciya Liao, Zhaohui Zheng
User behavior driven ranking without editorial judgments. CIKM (2010)
Taesup Moon, Alexander J. Smola, Yi Chang, Zhaohui Zheng
IntervalRank: isotonic regression with listwise and pairwise constraints. WSDM (2010)
Taesup Moon, Tsachy Weissman
Universal FIR MMSE Filtering. IEEE Trans. Signal Process. 57 (3) (2009)
Taesup Moon, Tsachy Weissman
Discrete denoising with shifts. IEEE Trans. Inf. Theory 55 (11) (2009)
Taesup Moon, Tsachy Weissman
Universal Filtering Via Hidden Markov Modeling. IEEE Trans. Inf. Theory 54 (2) (2008)
Taesup Moon, Tsachy Weissman
Competitive On-line Linear FIR MMSE Filtering. ISIT (2007)
Taesup Moon, Tsachy Weissman
Discrete Denoising with Shifts CoRR (2007)
Yejin Kim, Hyeon Bae, Kyungmin Poo, Jongrack Kim, Taesup Moon, Sungshin Kim, Changwon Kim
Soft Sensor Using PNN Model and Rule Base for Wastewater Treatment Plant. ISNN (2) (2006)
Taesup Moon, Tsachy Weissman
Universal Filtering via Hidden Markov Modeling CoRR (2006)
Taesup Moon, Tsachy Weissman
Discrete universal filtering via hidden Markov modelling. ISIT (2005)