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ORCIDSeulki Lee 0002
Person information
- affiliation: Ulsan National Institute of Science and Technology, South Korea
- affiliation (PhD 2021): University of North Carolina at Chapel Hill, NC, USA
Other persons with the same name
- Seulki Lee — disambiguation page
- Seulki Lee 0001 — Imec, Holst Centre, Eindhoven, The Netherlands (and 1 more)
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2020 – today
- 2025
[c15]Kwangryeol Park, Seulki Lee:
SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization. AAAI 2025: 19848-19856- 2024
- [c14]Jaewook Lee, Yoel Park
, Seulki Lee:
Designing Extremely Memory-Efficient CNNs for On-Device Vision Tasks. ACCV (8) 2024: 419-435 - [c13]Isu Jeong, Seulki Lee:
On-Demand Federated Learning for Arbitrary Target Class Distributions. AISTATS 2024: 3421-3429 - [c12]Jaeho Kim, Seok-Ju Hahn, Yoontae Hwang, Junghye Lee, Seulki Lee:
CAFO: Feature-Centric Explanation on Time Series Classification. KDD 2024: 1372-1382 - [i4]Jaeho Kim, Seok-Ju Hahn, Yoontae Hwang, Junghye Lee, Seulki Lee:
CAFO: Feature-Centric Explanation on Time Series Classification. CoRR abs/2406.01833 (2024) - [i3]Jaewook Lee, Yoel Park, Seulki Lee:
Designing Extremely Memory-Efficient CNNs for On-device Vision Tasks. CoRR abs/2408.03663 (2024) - [i2]Kwangryeol Park, Seulki Lee:
SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization. CoRR abs/2412.08894 (2024) - 2023
- [j2]Jaeho Kim, Hyewon Kang, Jaewan Yang, Haneul Jung, Seulki Lee, Junghye Lee:
Multitask Deep Learning for Human Activity, Speed, and Body Weight Estimation Using Commercial Smart Insoles. IEEE Internet Things J. 10(18): 16121-16133 (2023) - [c11]Seulki Lee:
MicroDeblur: Image Motion Deblurring on Microcontroller-based Vision Systems. IPSN 2023: 233-246 - [c10]Changhyeon Lee, Seulki Lee:
Softmax Output Approximation for Activation Memory-Efficient Training of Attention-based Networks. NeurIPS 2023 - [c9]Bosung Kim, Seulki Lee:
On-NAS: On-Device Neural Architecture Search on Memory-Constrained Intelligent Embedded Systems. SenSys 2023: 152-166 - 2022
- [c8]Seulki Lee, Shahriar Nirjon:
Weight Separation for Memory-Efficient and Accurate Deep Multitask Learning. PerCom 2022: 13-22 - 2021
- [b1]Seulki Lee:
Enabling Deep Intelligence on Embedded Systems. University of North Carolina, Chapel Hill, USA, 2021 - [c7]Seulki Lee, Shahriar Nirjon:
Deep Functional Network (DFN): Functional Interpretation of Deep Neural Networks for Intelligent Sensing Systems. IPSN 2021: 191-206 - 2020
- [c6]Seulki Lee, Shahriar Nirjon:
Fast and scalable in-memory deep multitask learning via neural weight virtualization. MobiSys 2020: 175-190 - [c5]Seulki Lee, Shahriar Nirjon:
SubFlow: A Dynamic Induced-Subgraph Strategy Toward Real-Time DNN Inference and Training. RTAS 2020: 15-29 - [c4]Seulki Lee, Shahriar Nirjon:
Learning in the Wild: When, How, and What to Learn for On-Device Dataset Adaptation. AIChallengeIoT@SenSys 2020: 34-40
2010 – 2019
- 2019
- [j1]Seulki Lee, Bashima Islam, Yubo Luo, Shahriar Nirjon:
Intermittent Learning: On-Device Machine Learning on Intermittently Powered System. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3(4): 141:1-141:30 (2019) - [c3]Bashima Islam, Yubo Luo, Seulki Lee, Shahriar Nirjon:
On-device training from sensor data on batteryless platforms: poster abstract. IPSN 2019: 325-326 - [c2]Seulki Lee, Shahriar Nirjon:
Neuro.ZERO: a zero-energy neural network accelerator for embedded sensing and inference systems. SenSys 2019: 138-152 - [i1]Seulki Lee, Bashima Islam, Yubo Luo, Shahriar Nirjon:
Intermittent Learning: On-Device Machine Learning on Intermittently Powered System. CoRR abs/1904.09644 (2019) - 2018
- [c1]Seulki Lee, Shahriar Nirjon:
Knowledge Transfer Between Embedded Controllers. DCOSS 2018: 61-68
Coauthor Index
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