Publications

• MT-GPD: A Saliency-Oriented Auxiliary Mechanism Design in Multimodal Deep Transfer Learning for Online Fake News Detection

  Zhang, Dongsong, Guohou Shan, Minwoo Lee, Lina Zhou, and Zhe Fu
  Production and Operations Management, 2025.
  

• Data-Driven Graph Construction of Power Flows in an Electric Power Transmission Network

  Benjamin Poole, Dulip Tharaka Madurasinghe, Christian K\"ummerle, Ganesh Kumar Venayagamoorthy, Minwoo Lee
  2024 International Conference on Machine Learning and Applications (ICMLA), 2024
  

• Conquering the Communication Constraints to Enable Large Pre-Trained Models in Federated Learning

  Guangyu Sun, , Umar Khalid, Matias Mendieta, Taojiannan Yang, Pu Wang, Minwoo Lee, Chen Chen
  arXiv preprint arXiv:2210.01708, 2024
  

• BAMM: Bidirectional Autoregressive Motion Model

  Ekkasit Pinyoanuntapong, Muhammad , Pu Wang, Minwoo Lee, Chen Chen
  European Conference on Computer Vision (ECCV), 2024
  

• Towards Interactive Reinforcement Learning with Intrinsic Feedback

  Benjamin Poole, Minwoo Lee
  NeuroComputing, 2024
  

• MMM: Generative Masked Motion Model

  Ekkasit Pinyoanuntapong, Ayman Ali, Pu Wang, Minwoo Lee, Chen Chen
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
  

• GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition

  Ekkasit Pinyoanuntapong, Ayman Ali, Kalvik Jakkala, Pu Wang, Minwoo Lee, Qucheng Peng, Chen Chen, Zhi Sun
  Proceedings of e 2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS), 2023
  

• GaitMixer: Skeleton-based Gait Representation Learning via Wide-spectrum Multi-axial Mixer

  Ekkasit Pinyoanuntapong, Aiman Ali, Pu Wang, Minwoo Lee, and Chen Chen.
  Proceedings of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.
  

• DHA-FL: Enabling Efficient and Effective AIoT via Decentralized Hierarchical Asynchronous Federated Learning

  Wesley Houston Huff, pinyarash pinyoanuntapong, Ravikumar Balakrishnan, Hao Feng, Minwoo Lee, Pu Wang, Chen Chen
  MLSys 2023 Workshop on Resource-Constrained Learning in Wireless Networks, 2023
  

• Error-related Potential Variability: Exploring the Effects on Classification and Transferability

  Benjamin Poole and Minwoo Lee
  IEEE Symposium on Computational Intelligence for Brain Computer Interfaces (CIBCI), Dec. 2022
  

• EdgeML: Towards network-accelerated federated learning over wireless edge

  Pinyarash Pinyoanuntapong, Prabhu Janakaraj, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, and Pu Wang
  Computer Networks, Vol. 219, Dec. 2022, 109396

• A Research Plan for Integrating Generative and Cognitive AI for Human Centered, Explainable Co-Creative AI

  Maher, M.L., Magerko, B., Ventura, D., Fisher, D., Cardona-Rivera, R., Fulda, N., Gero, J., Lee, M., Wilson, D., Kaufman.
  CHI 2022 Workshop on Generative AI and HCI, 2022 (https://generativeaiandhci.github.io/)

• Privacy Enhancement for Cloud-Based Few-Shot Learning

  Archit Parnami, Liyue Fan, Minwoo Lee
  Proceedings of the 2022 International Joint Conference on Neural Networks, 2022.
  

• Towards Scalable and Robust AIoT via Decentralized Federated Learning

  Pinyarash Pinyoanuntapong, Wesley Houston Huff, Minwoo Lee, Chen Chen, and Pu Wang
  IEEE Internet of Things Magazine, 2022
  

• Learning from Few Examples: A Summary of Approaches to Few-Shot Learning

  Archit Parnami and Minwoo Lee
  arXiv preprint arXiv:2203.04291, 2022
  

• Transformation of Node to Knowledge Graph Embeddings for Faster Link Prediction in Social Networks

  Archit Parnami, Mayuri Deshpande, Anant Kumar Mishra, Minwoo Lee
  Third International Workshop on Knowledge Graph Construction, 2022
  

• Detecting Face-to-Face Interactions with SocialBit: A Novel Algorithm for Wearables,

  White K, Reilly D, Scoleri G, Tate S, Mack C, Lee M, Mehl MR, Dhand A, Shin M
  Face2face: advancing the science of social interaction, The Royal Society, London, 2022.

• Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning

  Matias Mendieta, Taojiannan Yang, Pu Wang, Minwoo Lee, Zhengming Ding, Chen Chen
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 (Best Paper Nominee (33 out of 8,161))
  

• Few-Shot Keyword Spotting With Prototypical Networks

  Archit Parnami and Minwoo Lee
  ACM 7th International Conference on Machine Learning Technologies (ICMLT). 2022
  

• MutualNet: Adaptive ConvNet via Mutual Learning from Different Model Configurations

  Taojiannan Yang, Sijie Zhu, Matias Mendieta, Pu Wang, Ravikumar Balakrishnan, Minwoo Lee, Tao Han, Mubarak Shah, Chen Chen
  Transactions on Pattern Analysis and Machine Intelligence, 2022
  

• Sim-to-Real Transfer in Multi-agent ReinforcementNetworking for Federated Edge Computing

  Pinyarash Pinyoanuntapong, Tagore Pothuneedi, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, and Pu Wang
  IEEE SEC/EdgeComm (Invited Paper), 2021
  

• Multi-task Transfer with Practice.

  Upasana Pattnaik and Minwoo Lee.
  IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), 2021
  

• Learning Sparse Evidence-Driven Interpretation to Understand Deep Reinforcement Learning Agents.

  Giang Dao, Wesley Huff, and Minwoo Lee.
  IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), 2021
  

• Data-driven Safety Risk Prediction of Lithium-ion Battery

  Yikai Jia, Jiani Li1, Chunhao Yuan, Xiang Gao, Weiran Yao, Minwoo Lee, Jun Xu Advanced Energy Materials,p2003868, 2021
  

• Spatio-Temporal Domain Adaptation for Gait based User Identification from Radar Data

  Kalvik Jakkala, Pu Wang, Minwoo Lee, Chen Chen, Arupjyoti Bhuyan, and Zhi Sun, 2020
  

• Co-creative Robotic Arm for Differently-Abled Kids: Speech, Sketch Inputs and External Feedbacks for Multiple Drawings.

  Sharma Shaikh, Vidhushini Srinivasan, Yue Peng, Minwoo Lee, and Nicholas Davis. Proceedings of the Future Technologies Conference, 2020

• Demystifying Deep Neural Networks Through Interpretation: A Survey

  Giang Dao and Minwoo Lee
  arXiv preprint arXiv:2012.07119, 2020
  

• FedAir: Towards Multi-hop Federated Learning Over-the-Air

  Pinyarash Pinyoanuntapong, Prabhu Janakaraj, Minwoo Lee, Pu Wang, Chen Chen
  IEEE SPAWC, 2020
  

• Continuous reinforcement learning to adapt multi-objective optimization online for robot motion

  Kai Zhang, Sterling McLeod, Minwoo Lee, Jing Xiao
  International Journal of Advanced Robotic Systems, 2020
  

• Towards In-Band Telemetry for Self Driving Wireless Networks

  Prabhu Janakaraj, Pinyarash Pinyoanuntapong, Pu Wang, and Minwoo Lee
  2019 IEEE INFOCOM Workshop: NI 2020: Network Intelligence: Machine Learning for Networking, July 2020
  

• Efficient Practice for Deep Reinforcement Learning

  Venkata Sai Santosh Ravi Teja Kancharla and Minwoo Lee
  Proceedings of 2019 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL). Dec 2019
  

• Relevant Experiences in Replay Buffer

  Giang Dao and Minwoo Lee
  Proceedings of 2019 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL). Dec 2019
  

• Automatic Composite Action Discovery for Hierarchical Reinforcement Learning

  Josiah Laivins and Minwoo Lee
  Proceedings of 2019 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL). Dec 2019
  

• Distributed Multi-Hop Traffic Engineering via Stochastic Policy Gradient Reinforcement Learning

  Pinyarash Pinyoanuntapong, Minwoo Lee, and Pu Wang
  IEEE GLOBECOM, Dec 2019
  

• STAR: Simultaneous Tracking and Recognition Through Millimeter Waves and Deep Learning

  Prabhu Janakaraj, Kalvik Jakkala, Arupjyoti (Arup) Bhuyan, Zhi Sun, Pu Wang, Minwoo Lee
  2019 12th IFIP Wireless and Mobile Networking Conference (WMNC), 2019
  

• Delay-optimal traffic engineering through multi-agent reinforcement learning

  Pinyarash Pinyoanuntapong, Minwoo Lee, and Pu Wang
  2019 IEEE INFOCOM Workshop: NI 2019: Network Intelligence: Machine Learning for Networking, Apr 2019
  

• Deep CSI Learning for Gait Recognition At-Scale

  Kalvik Jakkala, Arupjyoti Bhuyan, Zhi Sun, Pu Wang , and Minwoo Lee, Proceedings of BalkanCom'19, Skopje, Macedonia, June 2019

• Topological Data Analysis for Discourse Semantics?

  Ketki Savle, Wlodek Zadrozny and Minwoo Lee.
  The 13th International Conference on Computational Semantics (IWCS'19), May 2019
  

• Deep Reinforcement Learning Monitor for Snapshot Recording.

  Giang Dao, Indrajeet Mishra, and Minwoo Lee.
  The 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA'18), December 2018
  
  

• Visual Sparse Bayesian Reinforcement Learning: A Framework for Interpreting What an Agent Has Learned.

  Indrajeet Mishra, Giang Dao and Minwoo Lee.
  Proceedings of 2018 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), 2018.

• Unstructured Medical Text Classification Using Linguistic Analysis: A Supervised Deep Learning Approach.

  Ahmad Al-Doulat, Islam Obaidat, and Minwoo Lee
  15th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2018), October 2018

• Deep Learning Based Urban Analytics Platform: Applications to Traffic Flow Modeling and Prediction.

  Archit Parnami, Prajval Bavi, Dimitris Papanikolaou, Srinivas Akella, Minwoo Lee and Siddharth Krishnan.
  ACM SIGKDD Workshop on Mining Urban Data (MUD3), London, UK, 2018

• Can Reinforcement Learning Agent Practice Before It Starts Learning?

  Minwoo Lee and Chuck Anderson.
  Proceedings of the 2017 International Joint Conference on Neural Networks, Alaska, USA, 2017.

• Relevance Vector Sampling for Reinforcement Learning in Continuous Action Space.

  Minwoo Lee and Chuck Anderson.
  The 15th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA'16), December 2016
  Related videos are available here.

• Robust Reinforcement Learning with Relevance Vector Machines.

  Minwoo Lee and Chuck Anderson.
  Robotics: Science and Systems (RSS) 2016 Robot Learning and Planning Workshop, June 2016

• Faster Reinforcement Learning After Pretraining Deep Networks to Predict State Dynamics.

  Chuck Anderson, Minwoo Lee, Dan Elliott.
  Proceedings of the 2015 International Joint Conference on Neural Networks, Killarney, Ireland, 2015.
  (Best Paper Award)

• Convergent Reinforcement Learning Control with Neural Networks and Continuous Action Search.

  Minwoo Lee and Chuck Anderson.
  Proceedings of 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), pp. 1-8, 2014.

• Automated Cyber-attack Scenario Generation Using the Symbolic Simulation.

  Jong-Keun Lee, Min-Woo Lee, Jang-Se Lee, Sung-Do Chi, and Syng-Yup Ohn.
  AIS 2004, lNAI 3397, pp. 380-389, 2004

• DEVS/HLA-Based Modeling and Simulation for Intelligent Transportation Systems.

  Jong-Keun Lee, Min-Woo Lee, Sung-Do Chi.
  SIMULATION, Vol 79, Issue 8, pp. 423-439, August, 2003.