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Hwanjun Song
Hwanjun Song
Research Scientist, NAVER AI Lab
Verified email at navercorp.com - Homepage
Title
Cited by
Cited by
Year
Learning from Noisy Labels with Deep Neural Networks: A Survey
H Song, M Kim, D Park, Y Shin, JG Lee
Transactions on Neural Networks and Learning Systems (TNNLS), 2022
2652022
SELFIE: Refurbishing Unclean Samples for Robust Deep Learning
H Song, M Kim, JG Lee
International Conference on Machine Learning (ICML), 2019
1642019
RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm based on Random Partitioning
H Song, JG Lee
International Conference on Management of Data (SIGMOD), 2018
532018
PAMAE: Parallel k-Medoids Clustering with High Accuracy and Efficiency
H Song, JG Lee, WS Han
International Conference on Knowledge Discovery and Data Mining (KDD), 2017
382017
Robust Learning by Self-Transition for Handling Noisy Labels
H Song, M Kim, D Park, Y Shin, JG Lee
International Conference on Knowledge Discovery and Data Mining (KDD), 2021
36*2021
Hi-Covidnet: Deep Learning Approach to Predict Inbound Covid-19 Patients and Case Study in South Korea
M Kim, J Kang, D Kim, H Song, H Min, Y Nam, D Park, JG Lee
International Conference on Knowledge Discovery and Data Mining (KDD), 2020
26*2020
ViDT: An Efficient and Effective Fully Transformer-based Object Detector
H Song, D Sun, S Chun, V Jampani, D Han, B Heo, W Kim, MH Yang
International Conference on Learning Representation (ICLR), 2022
132022
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective
SE Whang, Y Roh, H Song, JG Lee
arXiv preprint arXiv:2112.06409, 2021
102021
Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection
H Song, M Kim, S Kim, JG Lee
International Conference on Information and Knowledge Management (CIKM), 2020
92020
Ada-Boundary: Accelerating DNN Training via Adaptive Boundary Batch Selection
H Song, S Kim, M Kim, JG Lee
Machine Learning (ML), 2020
72020
Machine Learning Robustness, Fairness, and their Convergence
JG Lee, Y Roh, H Song, SE Whang
International Conference on Knowledge Discovery and Data Mining (KDD), 2021
52021
TRAP: Two-Level Regularized Autoencoder-based Embedding for Power-law Distributed Data
D Park, H Song, M Kim, JG Lee
The Web Conference (WWW), 2020
52020
PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation
M Kim, H Song, D Kim, S Kijung, JG Lee
AAAI Conference on Artificial Intelligence (AAAI), 2021
32021
Understanding Cross-domain Few-shot Learning: An Experimental Study
J Oh, S Kim, N Ho, JH Kim, H Song, SY Yun
Annual Conference on Neural Information Processing Systems (NeurIPS), 2022
22022
Dataset Condensation via Efficient Synthetic-Data Parameterization
JH Kim, J Kim, SJ Oh, S Yun, H Song, J Jeong, JW Ha, HO Song
International Conference on Machine Learning (ICML), 2022
22022
Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data
D Park, H Song, MS Kim, JG Lee
Advances in Neural Information Processing Systems (NeurIPS), 2021
22021
Coherence-based Label Propagation over Time Series for Accelerated Active Learning
Y Shin, S Yoon, S Kim, H Song, JG Lee, BS Lee
International Conference on Learning Representation (ICLR), 2022
12022
COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies
D Kim, H Min, Y Nam, H Song, S Yoon, M Kim, JG Lee
AAAI Conference on Artificial Intelligence (AAAI), 2022
12022
Revisit Prediction by Deep Survival Analysis
S Kim, H Song, S Kim, B Kim, JG Lee
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020
12020
Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning
D Park, Y Shin, J Bang, Y Lee, H Song, JG Lee
Annual Conference on Neural Information Processing Systems (NeurIPS), 2022
2022
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