SCARL: Attentive reinforcement learning-based scheduling in a multi-resource heterogeneous cluster M Cheong, H Lee, I Yeom, H Woo IEEE Access 7, 153432-153444, 2019 | 30 | 2019 |
Panda: Reinforcement learning-based priority assignment for multi-processor real-time scheduling H Lee, J Lee, I Yeom, H Woo IEEE Access 8, 185570-185583, 2020 | 20 | 2020 |
A global DAG task scheduler using deep reinforcement learning and graph convolution network H Lee, S Cho, Y Jang, J Lee, H Woo IEEE Access 9, 158548-158561, 2021 | 17 | 2021 |
Differentiable ranking metric using relaxed sorting for top-k recommendation H Lee, S Cho, Y Jang, J Kim, H Woo IEEE Access 9, 114649-114658, 2021 | 15 | 2021 |
An Efficient Combinatorial Optimization Model Using Learning-to-Rank Distillation H Woo, H Lee, S Cho Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022 | 5 | 2022 |
How Important is Periodic Model update in Recommender System? H Lee, S Yoo, D Lee, J Kim Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 3 | 2023 |
Simple and Efficient Recommendation Strategy for Warm/Cold Sessions for RecSys Challenge 2022 H Lee, S Yoo, A Yang, W Jang, C Park Proceedings of the Recommender Systems Challenge 2022, 50-54, 2022 | 1 | 2022 |
A Differentiable Ranking Metric Using Relaxed Sorting Operation for Top-K Recommender Systems H Lee, Y Jang, J Kim, H Woo arXiv preprint arXiv:2008.13141, 2020 | 1 | 2020 |
Fixed Priority Global Scheduling from a Deep Learning Perspective H Lee, M Wang, H Woo arXiv preprint arXiv:2012.03002, 2020 | | 2020 |