Taehyeon Kim
Taehyeon Kim
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Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation
T Kim, J Oh, NY Kim, S Cho, SY Yun
IJCAI 2021, 2021
FINE Samples for Learning with Noisy Labels
T Kim, J Ko, J Choi, S Cho, SY Yun
NeurIPS 2021, 2021
A Survey of Supernet Optimization and its Applications: Spatial and Temporal Optimization for Neural Architecture Search
S Cha, T Kim, H Lee, SY Yun
arXiv preprint arXiv:2204.03916, 2022
Revisiting orthogonality regularization: a study for convolutional neural networks in image classification
T Kim, SY Yun
IEEE Access 10, 69741-69749, 2022
Accurate and fast federated learning via combinatorial multi-armed bandits
T Kim, S Bae, J Lee, S Yun
arXiv, 2020
Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction
T Kim, N Ho, D Kim, SY Yun
arXiv, 2022
Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts
A Gruca, F Serva, L Lliso, P Rípodas, X Calbet, P Herruzo, J Pihrt, ...
NeurIPS 2022 Competition Track, 292-313, 2023
Supernet Training for Federated Image Classification under System Heterogeneity
T Kim, SY Yun
ICML 2022 Workshop: Dynamic Neural Networks (Oral), 2022
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
T Kim, J Kim, G Lee, SY Yun
ICLR 2024 (Spotlight), 2023
Efficient Model for Image Classification With Regularization Tricks
T Kim, J Kim, S Yun
NeurIPS 2019 Competition and Demonstration Track (PMLR 123), 2020
Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition
T Kim, S Kang, H Shin, D Yoon, S Eom, K Shin, SY Yun
NeurIPS 2022 Workshop: Weather4Cast Competition, 2022
Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search
T Kim, H Myeong, SY Yun
ICML 2022 Workshop: Hardware Aware Efficient Training (HAET), 2022
Adaptive Local Bayesian Optimization Over Multiple Discrete Variables
T Kim, J Ahn, N Kim, S Yun
NeurIPS 2020 Workshop at Competition Track: Black-Box Optimization Challenge, 2020
Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Federated Object Detection
T Kim, E Lin, J Lee, C Lau, V Mugunthan
NeurIPS 2023, 2023
Revisiting the Activation Function for Federated Image Classification
J Shin, T Kim, SY Yun
NeurIPS 2022 Workshop: Federated Learning, 2022
Layover Intermediate Layer for Multi-Label Classification in Efficient Transfer Learning
S Eom, T Kim, SY Yun
NeurIPS 2022 Workshop: Has it Trained Yet?, 2022
Towards Fast Inference: Exploring and Improving Blockwise Parallel Drafts
T Kim, AT Suresh, K Papineni, M Riley, S Kumar, A Benton
arXiv, 2024
Non-linear Fusion in Federated Learning: A Hypernetwork Approach to Federated Domain Generalization
M Bartholet, T Kim, A Beuret, SY Yun, JM Buhmann
arXiv, 2024
Revisiting Early-Learning Regularization When Federated Learning Meets Noisy Labels
T Kim, D Kim, SY Yun
arXiv, 2024
Leveraging Normalization Layer in Adapters With Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning
Y Yang, T Kim, SY Yun
AAAI 2024, 2023
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