Publications
Selected ML/AI-Related Papers
D.-Y. Kim, D.-E. Lee, J.-W. Kim, and H.-S. Lee, “Collaborative policy learning for dynamic scheduling tasks in cloud-edge-terminal IoT networks using federated reinforcement learning,” IEEE Internet of Things Journal, Vol. 11, No. 6, pp. 10133-10149, Mar. 2024 (10.1109/JIOT.2023.3327495). (JCR 2023, SCIE, Top 3.4%, IF 8.2)
J.-H. Lee, J.-Y. Park, H.-S. Sim, and H.-S. Lee, “Multi-residential energy scheduling under time-of-use and demand charge tariffs with federated reinforcement learning,” IEEE Transactions on Smart Grid, Vol. 14, No. 6, pp. 4360-4372, Nov. 2023 (10.1109/TSG.2023.3251956). (JCR 2023, SCIE, Top 5.0%, IF 8.6)
K. Min, Y. Kim, and H.-S. Lee, “Meta-scheduling framework with cooperative learning towards beyond 5G,” IEEE Journal on Selected Areas in Communications, Vol. 41, No. 6, pp. 1810-1824, June 2023 (10.1109/JSAC.2023.3273698). (JCR 2023, SCIE, Top 1.3%, IF 13.8)
S.-H. Hong and H.-S. Lee, “Robust energy management system with safe reinforcement learning using short-horizon forecasts,” IEEE Transactions on Smart Grid, Vol. 14, No. 3, pp. 2485-2488, May 2023 (10.1109/TSG.2023.3240588). (JCR 2023, SCIE, Top 5.0%, IF 8.6)
H.-S. Lee, D.-Y. Kim, and J.-W. Lee, “Radio and energy resource management in renewable energy-powered wireless networks with deep reinforcement learning,” IEEE Transactions on Wireless Communications, Vol. 21, No. 7, pp. 5435-5449, Jul. 2022 (10.1109/TWC.2022.3140731). (JCR 2023, SCIE, Top 3.6%, IF 8.9)
H.-S. Lee, “System-agnostic meta-learning for MDP-based dynamic scheduling via descriptive policy,” in Proc. AISTATS 2022, Mar. 2022. [ArXiv] (Major ML/AI Conference)
H.-S. Lee and J.-W. Lee, “Adaptive transmission scheduling in wireless networks for asynchronous federated learning,” IEEE Journal on Selected Areas in Communications, Vol. 39, No. 12, pp. 3673-3687, Dec. 2021 (10.1109/JSAC.2021.3118353). [ArXiv] (JCR 2023, SCIE, Top 1.3%, IF 13.8)
H.-S. Lee, “Channel metamodeling for explainable data-driven channel model,” IEEE Wireless Communications Letters, Vol. 10, No. 12, pp. 2678-2682, Dec. 2021 (10.1109/LWC.2021.3111874). [Paper] (JCR 2023, SCIE, Top 19.9%, IF 4.6)
H.-S. Lee, C. Shen, W. Zame, J.-W. Lee, and M. van der Schaar, “SDF-Bayes: Cautious optimism in safe dose-finding clinical trials with drug combinations and heterogeneous patient groups,” in Proc. AISTATS 2021, Apr. 2021. (Major ML/AI Conference)
H.-S. Lee, Y. Zhang, W. Zame, C. Shen, J.-W. Lee, and M. van der Schaar, “Robust recursive partitioning for heterogeneous treatment effects with uncertainty quantification,” in Proc. NeurIPS 2020, Dec. 2020. (Major ML/AI Conference)
H.-S. Lee, C. Shen, J. Jordon, and M. van der Schaar, “Contextual constrained learning for dose-finding clinical trials,” in Proc. AISTATS 2020, June 2020, Palermo, Italy. (Major ML/AI Conference)
H.-S. Lee and J.-W. Lee, “Contextual learning based wireless power transfer beam scheduling for IoT devices,” IEEE Internet of Things Journal, Vol. 5, No. 5, pp. 9606–9620, Dec. 2019. (JCR 2023, SCIE, Top 3.4%, IF 8.2)
Preprints
J. Won, H.-S. Lee, and J.-W. Lee, “A review on multi-fidelity hyperparameter optimization in machine learning,” submitted.
J. Shin, J. Won, H.-S. Lee, and J.-W. Lee, “A review on label cleaning techniques for learning with noisy labels,” in revision.
H.-S. Lee, D.-Y. Kim and K. Min, “Self-improving interference management based on deep learning with uncertainty quantification,” in revision.
K. Min, H.-S. Park, and H.-S. Lee, “Beam alignment in non-stationary environments using a novel time-varying structured bandits,” in revision.
International Journals
J.-W. Kim and H.-S. Lee, “Early exiting-aware joint resource allocation and DNN splitting for multi-sensor digital twin in edge-cloud collaborative systems,” to appear in IEEE Internet of Things Journal (10.1109/JIOT.2024.3439852). (JCR 2023, SCIE, Top 3.4%, IF 8.2)
H. Je-Gal, Y.-S. Park, S.-H. Park, J.-U. Kim, J.-H. Yang, S. Kim, and H.-S. Lee, “Time series explanatory fault prediction framework for marine main engine using explainable artificial intelligence,” Journal of Marine Science and Engineering, Vol. 12, No. 8, 1296, Jul. 2024 (10.3390/JMSE12081296). (JCR 2023, SCIE, IF 2.7, Q1)
K.-S. Kim and H.-S. Lee, “To exit or not to exit: Cost-effective early exit architecture based on Markov decision process,” Mathematics, Vol. 12, No. 14, 2263, Jul. 2024 (10.3390/math12142263). (JCR 2023, SCIE, Top 4.2%, IF 2.3)
H.-S. Lee, “Automated tariff design for energy supply-demand matching based on Bayesian optimization: Technical framework and policy implications,” Energy Policy, Vol. 188, 114102, May 2024 (10.1016/j.enpol.2024.114102). (JCR 2023, SSCI, Top 1.1%/SCIE, Top 6.8%, IF 9.3)
D.-Y. Kim, D.-E. Lee, J.-W. Kim, and H.-S. Lee, “Collaborative policy learning for dynamic scheduling tasks in cloud-edge-terminal IoT networks using federated reinforcement learning,” IEEE Internet of Things Journal, Vol. 11, No. 6, pp. 10133-10149, Mar. 2024 (10.1109/JIOT.2023.3327495). (JCR 2023, SCIE, Top 3.4%, IF 8.2)
H.-S. Lee, D.-Y. Kim, and K. Min, “Universal dynamic pilot allocation for beam alignment based on multi-armed bandits,” IEEE Wireless Communications Letters, Vol. 13, No. 3, pp 756-760, Mar. 2024 (10.1109/LWC.2023.3342738). (JCR 2023, SCIE, Top 19.9%, IF 4.6)
D.-Y. Kim, C.-B. Sohn, and H.-S. Lee, “Dynamic joint scheduling of anycast transmission and modulation in hybrid unicast-multicast SWIPT-based IoT sensor networks,” IEEE Sensors Journal, Vol. 23, No. 24, pp. 31345-31358, Dec. 2023 (10.1109/JSEN.2023.3329499). (JCR 2023, SCIE, Top 19.1%, IF 4.3)
J.-H. Lee, J.-Y. Park, H.-S. Sim, and H.-S. Lee, “Multi-residential energy scheduling under time-of-use and demand charge tariffs with federated reinforcement learning,” IEEE Transactions on Smart Grid, Vol. 14, No. 6, pp. 4360-4372, Nov. 2023 (10.1109/TSG.2023.3251956). (JCR 2023, SCIE, Top 5.0%, IF 8.6)
H. Je-Gal, S.-J. Lee, J.-H. Yoon, H.-S. Lee, J.-H. Yang, and S. Kim, “A novel time-frequency feature fusion approach for robust fault detection of marine main engine,” Journal of Marine Science and Engineering, Vol. 11, No. 8, 1577, Aug. 2023 (10.3390/JMSE11081577). (JCR 2023, SCIE, IF 2.7, Q1)
K. Min, Y. Kim, and H.-S. Lee, “Meta-scheduling framework with cooperative learning towards beyond 5G,” IEEE Journal on Selected Areas in Communications, Vol. 41, No. 6, pp. 1810-1824, June 2023 (10.1109/JSAC.2023.3273698). (JCR 2023, SCIE, Top 1.3%, IF 13.8)
H.-S. Lee, S. Moon, D.-Y. Kim, and J.-W. Lee, “Packet-based fronthauling in 5G networks: Network slicing-aware packetization,” IEEE Communications Standards Magazine, Vol. 7, No. 2, pp. 56-63, June 2023 (10.1109/MCOMSTD.0007.200062).
S.-H. Hong and H.-S. Lee, “Robust energy management system with safe reinforcement learning using short-horizon forecasts,” IEEE Transactions on Smart Grid, Vol. 14, No. 3, pp. 2485-2488, May 2023 (10.1109/TSG.2023.3240588). (JCR 2023, SCIE, Top 5.0%, IF 8.6)
H.-S. Lee, “Device selection and resource allocation for layerwise federated learning in wireless networks,” IEEE Systems Journal, Vol. 16, No. 4, pp. 6441-6444, Dec. 2022 (10.1109/JSYST.2022.3169461). (JCR 2023, SCIE, IF 4.0, Q1)
K.-W. Kim, H.-S. Lee, R. Zhang, and J.-W. Lee, “Contextual learning-based waveform scheduling for wireless power transfer with limited feedback,” IEEE Internet of Things Journal, Vol. 9, No. 17, pp. 15578-15592, Sep. 2022 (10.1109/JIOT.2022.3150798). (JCR 2023, SCIE, Top 3.4%, IF 8.2)
H.-S. Lee, D.-Y. Kim, and J.-W. Lee, “Radio and energy resource management in renewable energy-powered wireless networks with deep reinforcement learning,” IEEE Transactions on Wireless Communications, Vol. 21, No. 7, pp. 5435-5449, Jul. 2022 (10.1109/TWC.2022.3140731). (JCR 2023, SCIE, Top 3.6%, IF 8.9)
H.-S. Lee and D.-E. Lee, “Resource allocation in wireless networks with federated learning: Network adaptability and learning acceleration,” ICT Express, Vol. 8, No. 1, pp. 31-36, Mar. 2022 (10.1016/J.ICTE.2022.01.019). (JCR 2023, SCIE, IF 4.1, Q1)
H.-S. Lee, “Channel metamodeling for explainable data-driven channel model,” IEEE Wireless Communications Letters, Vol. 10, No. 12, pp. 2678-2682, Dec. 2021 (10.1109/LWC.2021.3111874). [Paper] (JCR 2023, SCIE, Top 19.9%, IF 4.6)
H.-S. Lee and J.-W. Lee, “Adaptive transmission scheduling in wireless networks for asynchronous federated learning,” IEEE Journal on Selected Areas in Communications, Vol. 39, No. 12, pp. 3673-3687, Dec. 2021 (10.1109/JSAC.2021.3118353). [ArXiv] (JCR 2023, SCIE, Top 1.3%, IF 13.8)
B.-H. Lee, H.-S. Lee, S. Moon, and J.-W. Lee, “Enhanced random access for massive machine type communications,” IEEE Internet of Things Journal, Vol. 8, No. 8, pp. 7046-7064, Apr. 2021. (JCR 2023, SCIE, Top 3.4%, IF 8.2)
H.-S. Lee and J.-W. Lee, “Adaptive wireless power transfer beam scheduling for non-static IoT devices using deep reinforcement learning,” IEEE Access, Vol. 8, pp. 206659-206673 Nov. 2020. (JCR 2023, SCIE, IF 3.4)
W. R. Zame, I. Bica, C. Shen, A. Curth, H.-S. Lee, S. Bailey, J. Weatherall, D. Wright, F. Bretz, M. van der Schaar, “Machine learning for clinical trials in the era of COVID-19,” Statistics in Biopharmaceutical Research – Special Issue on Covid-19, Vol. 12, No. 4, pp. 506-517, 2020.
K.-W. Kim, H.-S. Lee, and J.-W. Lee, “Opportunistic waveform scheduling for wireless power transfer with multiple devices,” IEEE Transactions on Wireless Communications, Vol. 19, No. 9, pp. 5651-5665, Sept. 2020. (JCR 2023, SCIE, Top 3.6%, IF 8.9)
H.-S. Lee, J.-Y. Kim, and J.-W. Lee, “Resource allocation in wireless networks with deep reinforcement learning: A circumstance-independent approach,” IEEE Systems Journal, Vol. 14, No. 2, pp. 2589-2592, June 2020. (JCR 2023, SCIE, IF 4.0, Q1)
H.-S. Lee and J.-W. Lee, “EHLinQ: Distributed scheduler for D2D communication with RF energy harvesting,” IEEE Systems Journal, Vol. 14, No. 2, pp. 2281-2292, June 2020. (JCR 2023, SCIE, IF 4.0, Q1)
H.-S. Lee and J.-W. Lee, “Adaptive traffic management and energy cooperation in renewable energy powered cellular networks,” IEEE Systems Journal, Vol. 14, No. 1, pp. 132-143, Mar. 2020. (JCR 2023, SCIE, IF 4.0, Q1)
H.-S. Lee and J.-W. Lee, “Contextual learning based wireless power transfer beam scheduling for IoT devices,” IEEE Internet of Things Journal, Vol. 5, No. 5, pp. 9606–9620, Dec. 2019. (JCR 2023, SCIE, Top 3.4%, IF 8.2)
D.-Y. Kim, H.-S. Lee, K.-W. Kim, and J.-W. Lee, “Dual amplitude shift keying with double half-wave rectifier for SWIPT,” IEEE Wireless Communications Letters, Vol. 8, No. 4, pp. 1020-1023, Aug. 2019. (JCR 2023, SCIE, Top 19.9%, IF 4.6)
H.-S. Lee and J.-W. Lee, “Resource and task scheduling for SWIPT IoT systems with renewable energy sources,” IEEE Internet of Things Journal, Vol. 6, No. 2, pp. 2729-2748, Apr. 2019. (JCR 2023, SCIE, Top 3.4%, IF 8.2)
K.-W. Kim, H.-S. Lee, and J.-W. Lee, “Waveform design for fair wireless power transfer with multiple energy harvesting devices,” IEEE Journal on Selected Areas in Communications, Vol. 37, No. 1, pp. 34-47, Jan. 2019. (JCR 2023, SCIE, Top 1.3%, IF 13.8)
S. Moon, H.-S. Lee, and J.-W. Lee, “SARA: Sparse code multiple access-applied random access for IoT devices,” IEEE Internet of Things Journal, Vol. 5, No. 4, pp. 3160-3174, Aug. 2018. (JCR 2023, SCIE, Top 3.4%, IF 8.2)
H.-S. Lee, C. Tekin, M. van der Schaar, and J.-W. Lee, “Adaptive contextual learning for unit commitment in microgrids with renewable energy sources,” IEEE Journal of Selected Topics in Signal Processing, Vol. 12, No. 4, pp. 688-702, Aug. 2018. (JCR 2023, SCIE, Top 4.4%, IF 8.7)
H.-S. Lee and J.-W. Lee, “Task offloading in heterogeneous mobile cloud computing: Modeling, analysis, and cloudlet deployment,” IEEE Access, Vol. 6, pp. 14908-14925, Mar. 2018. (JCR 2023, SCIE, IF 3.4)
H.-S. Lee and J.-W. Lee, “QC2LinQ: QoS and channel-aware distributed link scheduler for D2D communication,” IEEE Transactions on Wireless Communications, Vol. 15, No. 12, pp. 8565-8579, Dec. 2016. (JCR 2023, SCIE, Top 3.6%, IF 8.9)
International Conferences and Workshops
J.-W. Kim, K.-S. Kim, and H.-S. Lee, “LAB-CNN: LoD-specific attention-based branch convolutional neural network for digital twin,” in Proc. IEEE MetaCom 2024 (Meta-XP Workshop), Aug. 2024, Hong Kong, China.
S.-H. Park, H. Je-Gal, and H.-S. Lee, “A novel data-driven soft sensor in metaverse provisioning predictive credibility based on uncertainty quantification,” in Proc. IEEE MetaCom 2024 (Meta-XP Workshop), Aug. 2024, Hong Kong, China.
J. Shin, J. Won, H.-S. Lee, and J.-W. Lee, “Utilizing unclean samples with label correction in a neural network,” in Proc. ICEIC 2024, Taipei, Taiwan, Jan. 2024, pp. 796-797.
J.-W. Kim, H. Je-Gal, and H.-S. Lee, “Efficient federated digital twin synchronization in edge-cloud-collaborative system,” in Proc. IEEE MetaCom 2023 (Meta-XP Workshop), June 2023, Kyoto, Japan.
H.-S. Lee, “System-agnostic meta-learning for MDP-based dynamic scheduling via descriptive policy,” in Proc. AISTATS 2022, Mar. 2022. [ArXiv] (Major ML/AI Conference)
H.-S. Lee, C. Shen, W. Zame, J.-W. Lee, and M. van der Schaar, “SDF-Bayes: Cautious optimism in safe dose-finding clinical trials with drug combinations and heterogeneous patient groups,” in Proc. AISTATS 2021, Apr. 2021. (Major ML/AI Conference)
H.-S. Lee, Y. Zhang, W. Zame, C. Shen, J.-W. Lee, and M. van der Schaar, “Robust recursive partitioning for heterogeneous treatment effects with uncertainty quantification,” in Proc. NeurIPS 2020, Dec. 2020. (Major ML/AI Conference)
H.-S. Lee, C. Shen, J. Jordon, and M. van der Schaar, “Contextual constrained learning for dose-finding clinical trials,” in Proc. AISTATS 2020, June 2020, Palermo, Italy. (Major ML/AI Conference)
D.-H.Bae, H.-S. Lee, and J.-W. Lee, “Low Latency Uplink Transmission,” in Proc. ICEIC 2017, Jan. 2017, Phuket, Thailand.
H.-S. Lee, C. Tekin, M. van der Schaar, and J.-W. Lee, “Contextual learning for unit commitment with renewable energy sources,” in Proc. IEEE GlobalSIP 2016, Dec. 2016, Washington DC, USA.
H.-S. Lee and J.-W. Lee, “Energy cooperation and traffic management in cellular networks with renewable energy,” in Proc. IEEE Globecom 2016, Dec. 2016, Washington DC, USA.
H.-S. Lee and J.-W. Lee, “QoS and channel-aware distributed link scheduling for D2D communication,” in Proc. WiOpt 2016, May 2016, Arizona, USA.
H.-S. Lee, D.-H. Bae, and J.-W. Lee, “Energy or traffic: which one to transfer,” in Proc. IEEE VTC 2015-Fall, Sept. 2015, Boston, USA.
H.-S. Lee and J.-W. Lee, “QoS and channel-aware subchannel scheduling for D2D multicast communication,” in Proc. ITC-CSCC 2015, June 2015, Seoul, Korea.
Domestic Journals
- 김지완, 제갈홍, 이승진, 이현석, “강화학습 모델을 활용한 디지털 롤모델 트윈 연구,” 한국통신학회논문지, 48권, 2호, Feb., 2023.
- 배덕현, 이현석, 이장원, “이동통신망에서 저지연 상향링크 전송 기법,” 한국통신학회논문지, 42권, 1호, Jan., 2017.
Domestic Conferences And Workshops
- 이다은, 이현석, “메타버스에서의 지각적 어포던스 개선을 위한 강화학습 기반 실시간 추천 시스템 설계”, 한국통신학회 하계종합학술대회, June 2022.
- 김지완, 제갈홍, 이승진, 이현석, “강화학습 모델을 활용한 디지털 롤모델 트윈 연구”, 한국통신학회 하계종합학술대회, June 2022.
- 이현석, “자율트윈을 위한 연합학습 활용 방안 연구”, 한국인터넷정보학회 추계학술발표대회, Oct. 2021.
- 이현석, “Meijer G-함수를 활용한 딥러닝 기반 설명 가능한 패스로스 모델”, 한국 인공지능 학술대회, Dec. 2020. (최우수논문상)
- 김진영, 이현석, 이장원, “Q-learning을 이용한 무선 네트워크에서 패킷 스케줄링 기법”, 한국통신학회 추계종합학술대회, Nov. 2017.
- 이현석, 이장원, “5G 네트워크를 위한 C-RAN에서의 Function Split,” 통신정보 합동학술대회 (JCCI 2016), Apr. 2016.
- 송지훈, 이현석, 이장원, “Time-correlated Rayleigh fading 채널에서 멀티셀 OFDMA 네트워크의 opportunistic 스케쥴링에 관한 연구,” 한국통신학회 동계종합학술대회, Feb. 2015.
Patents
- J. Lee and H. Lee, “Apparatus and method for transmitting and receiving information and power in wireless communication system ,” U.S. Patent 11,533,093, Dec. 22, 2022
- E. Lee, H. Lee, D. Bae, J. Lee, and I. Byun, “Method for transmitting and receiving data in wireless communication system, and device therefor,” U.S. Patent 10,609,696, Mar. 31, 2020
- H. Noh, J. Lee, Y. Kim, H. Lee, Y. Kwak, and S. Moon, “Interface device and method in wireless communication network,” U.S. Patent 10,560,958, Feb. 11, 2020
- J.-W. Lee, D.-Y. Kim, H.-S. Lee, and K.-Y. Kim, “Apparatus and method for transmitting and receiving information and power in wireless communication system,” U.S. Patent 10,411,764, Sep. 10, 2019
- K. Park, H. Lee, J. Lee, and H. Ko, “Method of performing scheduling for D2D multicast communication in wireless communication system and apparatus therefor,” U.S. Patent 9,706,524, Jul. 11, 2017.