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Hwanjun Song

Learning from Noisy Labels with Deep Neural Networks: A Survey (TNNLS 2022)
Meta-Learning for Online Update of Recommender Systems (AAAI 2022)
COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies (AAAI 2022)
Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data (NeurIPS 2021)
Robust Learning by Self-Transition for Handling Noisy Labels (KDD 2021)
PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation (AAAI 2021)
Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection (CIKM 2020)
Ada-Boundary: Accelerating DNN Training via Adaptive Boundary Batch Selection (Machine Learning 2020, (SCI Expanded, impact factor: 2.672)
Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea (KDD 2020)
How Does Early Stopping Help Generalization against Label Noise? (ICMLW 2020)
TRAP: Two-level Regularized Autoencoder-based Embedding for Power-law Distributed Data (TheWebConf 2020)
SELFIE: Refurbishing Unclean Samples for Robust Deep Learning (ICML 2019)

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