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Embedded AI Lab, UNIST
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  • About
 

We are an exciting research group at the Department of Computer Science and Engineering (CSE) and Artificial Intelligence Graduate School (AIGS) at Ulsan National Institute of Science and Technology (UNIST). Our lab makes resource-constrained real-time and embedded sensing systems capable of learning, adapting, and evolving, which enables Embedded Artificial Intelligence (EAI or Embedded AI).

[AAAI 2025] SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization
11:59
[AAAI 2025] SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization
[ACCV 2024] Designing Extremely Memory-Efficient CNNs for On-device Vision Tasks (Best Application)
11:47
[ACCV 2024] Designing Extremely Memory-Efficient CNNs for On-device Vision Tasks (Best Application)
[KDD 2024] CAFO: Feature-Centric Explanation on Time Series Classification
11:31
[KDD 2024] CAFO: Feature-Centric Explanation on Time Series Classification
[AISTATS 2024] On-Demand Federated Learning for Arbitrary Target Class Distributions
7:38
[AISTATS 2024] On-Demand Federated Learning for Arbitrary Target Class Distributions
[SenSys 2023] On-NAS: On-Device Neural Architecture Search on Memory-Constrained Embedded Systems
13:58
[SenSys 2023] On-NAS: On-Device Neural Architecture Search on Memory-Constrained Embedded Systems
[NeurIPS 2023] Softmax Output Approximation for Activation Memory-Efficient Training of Attention...
4:51
[NeurIPS 2023] Softmax Output Approximation for Activation Memory-Efficient Training of Attention...
[PerCom 2022] Weight Separation for Memory Efficient and Accurate Deep Multitask Learning
26:18
[PerCom 2022] Weight Separation for Memory Efficient and Accurate Deep Multitask Learning
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