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ORCIDMinwoo Lee 0001
Person information
- affiliation: University of North Carolina at Charlotte (UNCC), Department of Computer Science, NC, USA
- affiliation (PhD 2017): Colorado State University, Fort Collins, CO, USA
Other persons with the same name
- Minwoo Lee (aka: MinWoo Lee, Min-Woo Lee, Min Woo Lee) — disambiguation page
- Minwoo Lee 0002
![[0000-0003-1132-9381]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-1132-9381")
— Imagination Garden Inc., Future Agriculture Team, Andong, Republic of Korea - Minwoo Lee 0003 — Seoul National University, Department of Electrical and Computer Engineering, Seoul, Korea
- Min-Woo Lee 0004 (aka: Minwoo Lee 0004) — Seoul National University of Science & Technology, Graduate School of NID Fusion Technology, Korea
- Minwoo Lee 0005 (aka: MinWoo Lee 0005) — Ajou University, Department of Military Digital Convergence, SuWon, South Korea
- Minwoo Lee 0006 — University of Houston, Hilton College of Hotel and Restaurant Management, TX, USA (and 2 more)
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2020 – today
- 2024
[i16]Ekkasit Pinyoanuntapong, Muhammad Usama Saleem, Pu Wang, Minwoo Lee, Srijan Das, Chen Chen:
BAMM: Bidirectional Autoregressive Motion Model. CoRR abs/2403.19435 (2024)- 2023
- [j3]Taojiannan Yang, Sijie Zhu, Matías Mendieta, Pu Wang, Ravikumar Balakrishnan, Minwoo Lee, Tao Han, Mubarak Shah, Chen Chen:
MutualNet: Adaptive ConvNet via Mutual Learning From Different Model Configurations. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 811-827 (2023) - [c24]Ekkasit Pinyoanuntapong, Ayman Ali, Pu Wang, Minwoo Lee, Chen Chen:
Gaitmixer: Skeleton-Based Gait Representation Learning Via Wide-Spectrum Multi-Axial Mixer. ICASSP 2023: 1-5 - [i15]Benjamin Poole, Minwoo Lee:
Error-related Potential Variability: Exploring the Effects on Classification and Transferability. CoRR abs/2301.06555 (2023) - [i14]Ekkasit Pinyoanuntapong, Ayman Ali, Kalvik Jakkala, Pu Wang, Minwoo Lee, Qucheng Peng, Chen Chen, Zhi Sun:
GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition. CoRR abs/2301.13384 (2023) - [i13]Ekkasit Pinyoanuntapong, Pu Wang, Minwoo Lee, Chen Chen:
MMM: Generative Masked Motion Model. CoRR abs/2312.03596 (2023) - 2022
- [j2]Pinyarash Pinyoanuntapong, Prabhu Janakaraj, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, Pu Wang:
EdgeML: Towards network-accelerated federated learning over wireless edge. Comput. Networks 219: 109396 (2022) - [j1]Pinyarash Pinyoanuntapong, Wesley Houston Huff, Minwoo Lee, Chen Chen, Pu Wang:
Toward Scalable and Robust AIoT via Decentralized Federated Learning. IEEE Internet Things Mag. 5(1): 30-35 (2022) - [c23]Matías Mendieta, Taojiannan Yang, Pu Wang, Minwoo Lee, Zhengming Ding, Chen Chen:
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning. CVPR 2022: 8387-8396 - [c22]Archit Parnami, Mayuri Deshpande, Anant Kumar Mishra, Minwoo Lee:
Transformation of Node to Knowledge Graph Embeddings for Faster Link Prediction in Social Networks. KGCW@ESWC 2022 - [c21]Archit Parnami, Minwoo Lee:
Few-Shot Keyword Spotting With Prototypical Networks. ICMLT 2022: 277-283 - [c20]Archit Parnami, Muhammad Usama, Liyue Fan, Minwoo Lee:
Privacy Enhancement for Cloud-Based Few-Shot Learning. IJCNN 2022: 1-10 - [c19]Benjamin Poole, Minwoo Lee:
Error-related Potential Variability: Exploring the Effects on Classification and Transferability. SSCI 2022: 193-200 - [i12]Archit Parnami, Minwoo Lee:
Learning from Few Examples: A Summary of Approaches to Few-Shot Learning. CoRR abs/2203.04291 (2022) - [i11]Archit Parnami, Muhammad Usama, Liyue Fan, Minwoo Lee:
Privacy Enhancement for Cloud-Based Few-Shot Learning. CoRR abs/2205.07864 (2022) - [i10]Ekkasit Pinyoanuntapong, Ayman Ali, Pu Wang, Minwoo Lee, Chen Chen:
GaitMixer: Skeleton-based Gait Representation Learning via Wide-spectrum Multi-axial Mixer. CoRR abs/2210.15491 (2022) - 2021
- [c18]Pinyarash Pinyoanuntapong, Tagore Pothuneedi, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, Pu Wang:
Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing. SEC 2021: 355-360 - [c17]Giang Dao, Wesley Houston Huff, Minwoo Lee:
Learning Sparse Evidence- Driven Interpretation to Understand Deep Reinforcement Learning Agents. SSCI 2021: 1-7 - [c16]Upasana Pattnaik, Minwoo Lee:
Multi-task Transfer with Practice. SSCI 2021: 1-8 - [i9]Taojiannan Yang, Sijie Zhu, Matías Mendieta, Pu Wang, Ravikumar Balakrishnan, Minwoo Lee, Tao Han, Mubarak Shah, Chen Chen:
MutualNet: Adaptive ConvNet via Mutual Learning from Different Model Configurations. CoRR abs/2105.07085 (2021) - [i8]Pinyarash Pinyoanuntapong, Tagore Pothuneedi, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, Pu Wang:
Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing. CoRR abs/2110.08952 (2021) - [i7]Archit Parnami, Mayuri Deshpande, Anant Kumar Mishra, Minwoo Lee:
Transformation of Node to Knowledge Graph Embeddings for Faster Link Prediction in Social Networks. CoRR abs/2111.09308 (2021) - [i6]Pinyarash Pinyoanuntapong, Prabhu Janakaraj, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, Pu Wang:
EdgeML: Towards Network-Accelerated Federated Learning over Wireless Edge. CoRR abs/2111.09410 (2021) - [i5]Matías Mendieta, Taojiannan Yang, Pu Wang, Minwoo Lee, Zhengming Ding, Chen Chen:
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning. CoRR abs/2111.14213 (2021) - [i4]Benjamin Poole, Minwoo Lee:
Towards Intrinsic Interactive Reinforcement Learning: A Survey. CoRR abs/2112.01575 (2021) - 2020
- [c15]Prabhu Janakaraj, Pinyarash Pinyoanuntapong, Pu Wang, Minwoo Lee:
Towards In-Band Telemetry for Self Driving Wireless Networks. INFOCOM Workshops 2020: 766-773 - [c14]Pinyarash Pinyoanuntapong, Prabhu Janakaraj, Pu Wang, Minwoo Lee, Chen Chen:
FedAir: Towards Multi-hop Federated Learning Over-the-Air. SPAWC 2020: 1-5 - [i3]Archit Parnami, Minwoo Lee:
Few-Shot Keyword Spotting With Prototypical Networks. CoRR abs/2007.14463 (2020) - [i2]Giang Dao, Minwoo Lee:
Demysifying Deep Neural Networks Through Interpretation: A Survey. CoRR abs/2012.07119 (2020)
2010 – 2019
- 2019
- [c13]Ahmad Al-Doulat, Islam Obaidat, Minwoo Lee:
Unstructured Medical Text Classification using Linguistic Analysis: A Supervised Deep Learning Approach. AICCSA 2019: 1-7 - [c12]Pinyarash Pinyoanuntapong, Minwoo Lee, Pu Wang:
Distributed Multi-Hop Traffic Engineering via Stochastic Policy Gradient Reinforcement Learning. GLOBECOM 2019: 1-6 - [c11]Pinyarash Pinyoanuntapong, Minwoo Lee, Pu Wang:
Delay-Optimal Traffic Engineering through Multi-agent Reinforcement Learning. INFOCOM Workshops 2019: 435-442 - [c10]Prabhu Janakaraj, Kalvik Jakkala, Arupjyoti Bhuyan, Zhi Sun, Pu Wang, Minwoo Lee:
STAR: Simultaneous Tracking and Recognition through Millimeter Waves and Deep Learning. WMNC 2019: 211-218 - [c9]Venkata Sai Santosh Ravi Teja Kancharla, Minwoo Lee:
Efficient Practice for Deep Reinforcement Learning. SSCI 2019: 77-84 - [c8]Giang Dao, Minwoo Lee:
Relevant Experiences in Replay Buffer. SSCI 2019: 94-101 - [c7]Josiah Laivins, Minwoo Lee:
Automatic Composite Action Discovery for Hierarchical Reinforcement Learning. SSCI 2019: 198-205 - 2018
- [c6]Giang Dao, Indrajeet Mishra, Minwoo Lee:
Deep Reinforcement Learning Monitor for Snapshot Recording. ICMLA 2018: 591-598 - [c5]Indrajeet Mishra, Giang Dao, Minwoo Lee:
Visual Sparse Bayesian Reinforcement Learning: A Framework for Interpreting What an Agent Has Learned. SSCI 2018: 1427-1434 - 2017
- [c4]Minwoo Lee, Charles W. Anderson:
Can a reinforcement learning agent practice before it starts learning? IJCNN 2017: 4006-4013 - 2016
- [c3]Minwoo Lee, Charles W. Anderson:
Relevance Vector Sampling for Reinforcement Learning in Continuous Action Space. ICMLA 2016: 774-779 - [i1]Nancy M. Amato, Charles Anderson, Gregory S. Chirikjian, Hamidreza Chitsaz, Vishnu R. Desaraju, Chinwe Ekenna, Kris K. Hauser, Geoffrey A. Hollinger, Reza Iraji, Minwoo Lee, Qianli Ma, Seth McCammon, Nathan Michael, Shawna L. Thomas, Diane Uwacu, Yan Yan:
Proceedings of the 1st International Workshop on Robot Learning and Planning (RLP 2016). CoRR abs/1610.02573 (2016) - 2015
- [c2]Charles W. Anderson, Minwoo Lee, Daniel L. Elliott:
Faster reinforcement learning after pretraining deep networks to predict state dynamics. IJCNN 2015: 1-7 - 2014
- [c1]Minwoo Lee, Charles W. Anderson:
Convergent reinforcement learning control with neural networks and continuous action search. ADPRL 2014: 1-8
Coauthor Index
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last updated on 2024-05-28 23:21 CEST by the dblp team
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