News
2024
[2024 May] The article “Automated tariff design for energy supply-demand matching based on Bayesian optimization: Technical framework and policy implications” has been published in Energy Policy. [Link]
[2024 Mar.] The article “Automated tariff design for energy supply-demand matching based on Bayesian optimization: Technical framework and policy implications” has been accepted in Energy Policy.
[2024 Mar.] The article “Collaborative policy learning for dynamic scheduling tasks in cloud-edge-terminal IoT networks using federated reinforcement learning” has been published in IEEE Internet of Things Journal. [Link]
[2024 Mar.] The article “Universal dynamic pilot allocation for beam alignment based on multi-armed bandits” has been published in IEEE Wireless Communications Letters. [Link]
2023
[2023 Dec.] The article “IoT sensor and modulation scheduling for SWIPT using dual amplitude shift keying with double half-wave rectifier” has been published in IEEE Sensors Journal. [Link]
[2023 Dec.] The article “Universal dynamic pilot allocation for beam alignment based on multi-armed bandits” has been accepted in IEEE Wireless Communications Letters.
[2023 Oct.] The article “IoT sensor and modulation scheduling for SWIPT using dual amplitude shift keying with double half-wave rectifier” has been accepted in IEEE Sensors Journal.
[2023 Oct.] The article “Multi-residential energy scheduling under time-of-use and demand charge tariffs with federated reinforcement learning” has been published in IEEE Transactions on Smart Grid. [Link]
[2023 Oct.] The article “Collaborative policy learning for dynamic scheduling tasks in cloud-edge-terminal IoT networks using federated reinforcement learning” has been accepted in IEEE Internet of Things Journal. [Link]
[2023 Aug.] The article “A novel time-frequency feature fusion approach for robust fault detection of marine main engine” has been accepted and published in Journal of Marine Science and Engineering. [Link]
[2023 June] The article “Packet-based fronthauling in 5G networks: Network slicing-aware packetization” has been published in IEEE Communications Standards Magazine. [Link]
[2023 June] The article “Meta-scheduling framework with cooperative learning towards beyond 5G” has been published in IEEE Journal on Selected Areas in Communications. [Link]
[2023 Apr.] The article “Robust energy management system with safe reinforcement learning using short-horizon forecasts” has been published in IEEE Transactions on Smart Grid. [Link]
[2023 Apr.] The article “Meta-scheduling framework with cooperative learning towards beyond 5G” has been accepted in IEEE Journal on Selected Areas in Communications. [Link]
2022
[2022 Dec.] The paper “Device selection and resource allocation for layerwise federated learning in wireless networks” has been published in IEEE Systems Journal.
[2022 Aug.] The paper “Contextual learning-based waveform scheduling for wireless power transfer with limited feedback” has been published in IEEE Internet of Things Journal. [Link]
[2022 Jul.] The article “Packet-based fronthauling in 5G networks: Network slicing-aware packetization” has been accepted in IEEE Communications Standards Magazine.
[2022 Jul.] The paper “Radio and Energy Resource Management in Renewable Energy-Powered Wireless Networks With Deep Reinforcement Learning” has been published in IEEE Transactions on Wireless Communications. [Link]
[2022 Apr.] The paper “Device selection and resource allocation for layerwise federated learning in wireless networks” has been accepted in IEEE Systems Journal.
[2022 Mar.] The paper “Resource allocation in wireless networks with federated learning: Network adaptability and learning acceleration” has been published in ICT Express. [Link]
[2022 Feb.] The paper “Contextual learning-based waveform scheduling for wireless power transfer with limited feedback” has been accepted in IEEE Internet of Things Journal. [Link]
[2022 Jan.] The paper “Resource allocation in wireless networks with federated learning: Network adaptability and learning acceleration” has been accepted in ICT Express. [Link]
[2022 Jan.] The paper “System-agnostic meta-learning for MDP-based dynamic scheduling via descriptive policy” has been accepted in 25th International Conference on Artificial Intelligence and Statistics (AISTATS) 2022. [Arxiv]
2021
[2021 Dec.] The paper “Radio and Energy Resource Management in Renewable Energy-Powered Wireless Networks with Deep Reinforcement Learning” has been accepted in IEEE Transactions on Wireless Communications.
[2021 Dec.] The paper “Channel Metamodeling for Explainable Data-Driven Channel Model” has been published in IEEE Wireless Communications Letters. [Link]
[2021 Nov.] The paper “Adaptive transmission scheduling in wireless networks for asynchronous federated learning” has been published in IEEE Journal on Selected Areas in Communications. [Link]
- [2021 Sep.] The paper “Channel Metamodeling for Explainable Data-Driven Channel Model” has been accepted in IEEE Wireless Communications Letters. [Paper]
[2021 Aug.] The paper “Adaptive transmission scheduling in wireless networks for asynchronous federated learning” has been accepted in IEEE Journal on Selected Areas in Communications. [ArXiv]
[2021 Jul.] Our group has been joined the ITRC project “A Research on Core Technology of Autonomous Twins for Metaverse”.
[2021 June] A new research project “Machine Learning-Based Scheduling in Cellular Networks” has been started.
[2021 Apr.] The paper “Enhanced random access for massive machine type communications” has been published in IEEE Internet of Things Journal. [Link]
[2021 Mar.] A new research project “Explainable Artificial Intelligence (XAI) for Radio Resource Management in 6G Wireless Networks” has been started.
[2021 Jan.] The paper “SDF-Bayes: Cautious optimism in safe dose-finding clinical trials with drug combinations and heterogeneous patient groups” has been accepted in 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021. [Arxiv]
2020
[2020 Dec.] Our paper won the best paper award from 1st Korea AI Conference.
[2020 Dec.] The paper “Robust recursive partitioning for heterogeneous treatment effects with uncertainty quantification” has been presented at Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2020. [Link]
[2020 Nov.] The paper “Enhanced random access for massive machine type communications” has been accepted in IEEE Internet of Things Journal. [Link]
[2020 Nov.] The paper “Adaptive wireless power transfer beam scheduling for non-static IoT devices using deep reinforcement learning” has been published in IEEE Access. [Link]
[2020 Sept.] Prof. Lee has joined the School of Intelligent Mechatronics Engineering at Sejong University as an assistant professor.