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Taesup Kim
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2020 – today
- 2024
- [c21]Kyubyung Chae, Jaepill Choi, Yohan Jo, Taesup Kim:
Mitigating Hallucination in Abstractive Summarization with Domain-Conditional Mutual Information. NAACL-HLT (Findings) 2024: 1809-1820 - [i21]Namju Kwak, Taesup Kim:
X-PEFT: eXtremely Parameter-Efficient Fine-Tuning for Extreme Multi-Profile Scenarios. CoRR abs/2401.16137 (2024) - [i20]Jinha Park, Wonguk Cho, Taesup Kim:
Overcoming Data Inequality across Domains with Semi-Supervised Domain Generalization. CoRR abs/2403.05209 (2024) - [i19]Kyubyung Chae, Jaepill Choi, Yohan Jo, Taesup Kim:
Mitigating Hallucination in Abstractive Summarization with Domain-Conditional Mutual Information. CoRR abs/2404.09480 (2024) - [i18]Donggeun Kim, Taesup Kim:
Missing Modality Prediction for Unpaired Multimodal Learning via Joint Embedding of Unimodal Models. CoRR abs/2407.12616 (2024) - 2023
- [j2]Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani:
Flexible Model Aggregation for Quantile Regression. J. Mach. Learn. Res. 24: 162:1-162:45 (2023) - [c20]Minchang Kim, Yongjin Yang, Jung Hyun Ryu, Taesup Kim:
Meta-Learning with Adaptive Weighted Loss for Imbalanced Cold-Start Recommendation. CIKM 2023: 1077-1086 - [c19]Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor:
Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges. CoLLAs 2023: 89-119 - [c18]Suhyun Kang, Duhun Hwang, Moonjung Eo, Taesup Kim, Wonjong Rhee:
Meta-Learning with a Geometry-Adaptive Preconditioner. CVPR 2023: 16080-16090 - [c17]Wonguk Cho, Jinha Park, Taesup Kim:
Complementary Domain Adaptation and Generalization for Unsupervised Continual Domain Shift Learning. ICCV 2023: 11408-11418 - [i17]Minchang Kim, Yongjin Yang, Jung Hyun Ryu, Taesup Kim:
Meta-Learning with Adaptive Weighted Loss for Imbalanced Cold-Start Recommendation. CoRR abs/2302.14640 (2023) - [i16]Wonguk Cho, Jinha Park, Taesup Kim:
Complementary Domain Adaptation and Generalization for Unsupervised Continual Domain Shift Learning. CoRR abs/2303.15833 (2023) - [i15]Suhyun Kang, Duhun Hwang, Moonjung Eo, Taesup Kim, Wonjong Rhee:
Meta-Learning with a Geometry-Adaptive Preconditioner. CoRR abs/2304.01552 (2023) - 2022
- [c16]Jaeseong Lee, Seung-won Hwang, Taesup Kim:
FAD-X: Fusing Adapters for Cross-lingual Transfer to Low-Resource Languages. AACL/IJCNLP (2) 2022: 57-64 - [c15]Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J. Smola:
Faster Deep Reinforcement Learning with Slower Online Network. NeurIPS 2022 - [c14]Martin Klissarov, Rasool Fakoor, Jonas W. Mueller, Kavosh Asadi, Taesup Kim, Alexander J. Smola:
Adaptive Interest for Emphatic Reinforcement Learning. NeurIPS 2022 - [i14]Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor:
Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline. CoRR abs/2205.14495 (2022) - 2021
- [c13]Taesup Kim, Sungwoong Kim, Yoshua Bengio:
Visual Concept Reasoning Networks. AAAI 2021: 8172-8180 - [i13]Taesup Kim, Rasool Fakoor, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani:
Deep Quantile Aggregation. CoRR abs/2103.00083 (2021) - 2020
- [i12]Taesup Kim, Sungwoong Kim, Yoshua Bengio:
Visual Concept Reasoning Networks. CoRR abs/2008.11783 (2020)
2010 – 2019
- 2019
- [c12]Jongmin Kim, Taesup Kim, Sungwoong Kim, Chang D. Yoo:
Edge-Labeling Graph Neural Network for Few-Shot Learning. CVPR 2019: 11-20 - [c11]Sungwoong Kim, Ildoo Kim, Sungbin Lim, Woonhyuk Baek, Chiheon Kim, Hyungjoo Cho, Boogeon Yoon, Taesup Kim:
Scalable Neural Architecture Search for 3D Medical Image Segmentation. MICCAI (3) 2019: 220-228 - [c10]Sungbin Lim, Ildoo Kim, Taesup Kim, Chiheon Kim, Sungwoong Kim:
Fast AutoAugment. NeurIPS 2019: 6662-6672 - [c9]Taesup Kim, Sungjin Ahn, Yoshua Bengio:
Variational Temporal Abstraction. NeurIPS 2019: 11566-11575 - [i11]Sungbin Lim, Ildoo Kim, Taesup Kim, Chiheon Kim, Sungwoong Kim:
Fast AutoAugment. CoRR abs/1905.00397 (2019) - [i10]Jongmin Kim, Taesup Kim, Sungwoong Kim, Chang D. Yoo:
Edge-labeling Graph Neural Network for Few-shot Learning. CoRR abs/1905.01436 (2019) - [i9]Sungwoong Kim, Ildoo Kim, Sungbin Lim, Woonhyuk Baek, Chiheon Kim, Hyungjoo Cho, Boogeon Yoon, Taesup Kim:
Scalable Neural Architecture Search for 3D Medical Image Segmentation. CoRR abs/1906.05956 (2019) - [i8]Taesup Kim, Sungjin Ahn, Yoshua Bengio:
Variational Temporal Abstraction. CoRR abs/1910.00775 (2019) - 2018
- [c8]Inchul Song, Junyoung Chung, Taesup Kim, Yoshua Bengio:
Dynamic Frame Skipping for Fast Speech Recognition in Recurrent Neural Network Based Acoustic Models. ICASSP 2018: 4984-4988 - [c7]Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, Nate Kushman:
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. ICLR (Poster) 2018 - [c6]Hanwook Chung, Taesup Kim, Eric Plourde, Benoît Champagne:
Noise-adaptive Deep Neural Network for single-channel speech enhancement. MLSP 2018: 1-6 - [c5]Jaesik Yoon, Taesup Kim, Ousmane Dia, Sungwoong Kim, Yoshua Bengio, Sungjin Ahn:
Bayesian Model-Agnostic Meta-Learning. NeurIPS 2018: 7343-7353 - [i7]Iulian Vlad Serban, Chinnadhurai Sankar, Mathieu Germain, Saizheng Zhang, Zhouhan Lin, Sandeep Subramanian, Taesup Kim, Michael Pieper, Sarath Chandar, Nan Rosemary Ke, Sai Rajeswar, Alexandre de Brébisson, Jose M. R. Sotelo, Dendi Suhubdy, Vincent Michalski, Alexandre Nguyen, Joelle Pineau, Yoshua Bengio:
A Deep Reinforcement Learning Chatbot (Short Version). CoRR abs/1801.06700 (2018) - [i6]Taesup Kim, Jaesik Yoon, Ousmane Dia, Sungwoong Kim, Yoshua Bengio, Sungjin Ahn:
Bayesian Model-Agnostic Meta-Learning. CoRR abs/1806.03836 (2018) - 2017
- [c4]Taesup Kim, Inchul Song, Yoshua Bengio:
Dynamic Layer Normalization for Adaptive Neural Acoustic Modeling in Speech Recognition. INTERSPEECH 2017: 2411-2415 - [i5]Taesup Kim, Inchul Song, Yoshua Bengio:
Dynamic Layer Normalization for Adaptive Neural Acoustic Modeling in Speech Recognition. CoRR abs/1707.06065 (2017) - [i4]Iulian Vlad Serban, Chinnadhurai Sankar, Mathieu Germain, Saizheng Zhang, Zhouhan Lin, Sandeep Subramanian, Taesup Kim, Michael Pieper, Sarath Chandar, Nan Rosemary Ke, Sai Mudumba, Alexandre de Brébisson, Jose Sotelo, Dendi Suhubdy, Vincent Michalski, Alexandre Nguyen, Joelle Pineau, Yoshua Bengio:
A Deep Reinforcement Learning Chatbot. CoRR abs/1709.02349 (2017) - [i3]Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, Nate Kushman:
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. CoRR abs/1710.10766 (2017) - 2016
- [i2]Rodrigo Nogueira, Taesup Kim, Abdel-rahman Mohamed, Ahmed Hassan Awadallah, Pushmeet Kohli, Ahmed Mohamed:
MSR System Description - TAC 2016 KBP Cold Start Slof Filling Track. TAC 2016 - [i1]Taesup Kim, Yoshua Bengio:
Deep Directed Generative Models with Energy-Based Probability Estimation. CoRR abs/1606.03439 (2016) - 2012
- [c3]Kangsun Lee, Taesup Kim:
Reusing Simulation Models for Weapons Effectiveness Analysis. SIMULTECH 2012: 114-119 - 2011
- [c2]Taesup Kim, Sebastian Nowozin, Pushmeet Kohli, Chang D. Yoo:
Variable grouping for energy minimization. CVPR 2011: 1913-1920 - 2010
- [c1]Kyu Cheol Cho, Sung-Ho Jang, Chang Hyeon Noh, Tae-young Kim, Jong Sik Lee, Jae Min Lee, Taesup Kim, Kangsun Lee:
Route reasoning-based mobility modeling and simulation for street fight using DEVS. SummerSim 2010: 195-200
2000 – 2009
- 2009
- [j1]Hakjae Kim, Ryong Oh, Sungju Lee, Taesup Kim, Sangjoon Lee, Yongwha Chung, Choong-Ho Cho:
A fingerprint-based user authentication protocol considering both the mobility and security in the telematics environment. Comput. Stand. Interfaces 31(6): 1098-1107 (2009)
Coauthor Index
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last updated on 2024-09-13 01:38 CEST by the dblp team
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