Minwoo Lee

Orcid: 0000-0002-6860-608X

Affiliations:
  • University of North Carolina at Charlotte (UNCC), Department of Computer Science, NC, USA
  • Colorado State University, Fort Collins, CO, USA (PhD 2017)


According to our database1, Minwoo Lee authored at least 35 papers between 2011 and 2024.

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Bibliography

2024
BAMM: Bidirectional Autoregressive Motion Model.
Proceedings of the Computer Vision - ECCV 2024, 2024

MMM: Generative Masked Motion Model.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
MutualNet: Adaptive ConvNet via Mutual Learning From Different Model Configurations.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition.
CoRR, 2023

Gaitmixer: Skeleton-Based Gait Representation Learning Via Wide-Spectrum Multi-Axial Mixer.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Toward Scalable and Robust AIoT via Decentralized Federated Learning.
IEEE Internet Things Mag., 2022

Learning from Few Examples: A Summary of Approaches to Few-Shot Learning.
CoRR, 2022

EdgeML: Towards network-accelerated federated learning over wireless edge.
Comput. Networks, 2022

Error-related Potential Variability: Exploring the Effects on Classification and Transferability.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Privacy Enhancement for Cloud-Based Few-Shot Learning.
Proceedings of the International Joint Conference on Neural Networks, 2022

Few-Shot Keyword Spotting With Prototypical Networks.
Proceedings of the ICMLT 2022: 7th International Conference on Machine Learning Technologies, Rome, Italy, March 11, 2022

Transformation of Node to Knowledge Graph Embeddings for Faster Link Prediction in Social Networks.
Proceedings of the 3rd International Workshop on Knowledge Graph Construction (KGCW 2022) co-located with 19th Extended Semantic Web Conference (ESWC 2022), 2022

Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Towards Intrinsic Interactive Reinforcement Learning: A Survey.
CoRR, 2021

Multi-task Transfer with Practice.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Learning Sparse Evidence- Driven Interpretation to Understand Deep Reinforcement Learning Agents.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing.
Proceedings of the 6th IEEE/ACM Symposium on Edge Computing, 2021

2020
Demysifying Deep Neural Networks Through Interpretation: A Survey.
CoRR, 2020

FedAir: Towards Multi-hop Federated Learning Over-the-Air.
Proceedings of the 21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2020

Towards In-Band Telemetry for Self Driving Wireless Networks.
Proceedings of the 39th IEEE Conference on Computer Communications, 2020

2019
Automatic Composite Action Discovery for Hierarchical Reinforcement Learning.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Efficient Practice for Deep Reinforcement Learning.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Relevant Experiences in Replay Buffer.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

STAR: Simultaneous Tracking and Recognition through Millimeter Waves and Deep Learning.
Proceedings of the 12th IFIP Wireless and Mobile Networking Conference, 2019

Delay-Optimal Traffic Engineering through Multi-agent Reinforcement Learning.
Proceedings of the IEEE INFOCOM 2019, 2019

Distributed Multi-Hop Traffic Engineering via Stochastic Policy Gradient Reinforcement Learning.
Proceedings of the 2019 IEEE Global Communications Conference, 2019

Unstructured Medical Text Classification using Linguistic Analysis: A Supervised Deep Learning Approach.
Proceedings of the 16th IEEE/ACS International Conference on Computer Systems and Applications, 2019

2018
Visual Sparse Bayesian Reinforcement Learning: A Framework for Interpreting What an Agent Has Learned.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Deep Reinforcement Learning Monitor for Snapshot Recording.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

2017
Can a reinforcement learning agent practice before it starts learning?
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016
Proceedings of the 1st International Workshop on Robot Learning and Planning (RLP 2016).
CoRR, 2016

Relevance Vector Sampling for Reinforcement Learning in Continuous Action Space.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

2015
Faster reinforcement learning after pretraining deep networks to predict state dynamics.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
Convergent reinforcement learning control with neural networks and continuous action search.
Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014

2011
Hurricane Prediction with Python.
Proceedings of the 10th Python in Science Conference 2011 (SciPy 2011), Austin, Texas, July 11, 2011


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