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Xiaozhe Gu
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2020 – today
- 2025
- [j7]Xiaozhe Gu, Zixun Zhang, Ran Jin, Rick Siow Mong Goh, Tao Luo:
Self-distillation with model averaging. Inf. Sci. 694: 121694 (2025) - 2024
- [j6]Zhehui Wang, Xiaozhe Gu, Rick Siow Mong Goh, Joey Tianyi Zhou, Tao Luo:
Efficient Spiking Neural Networks With Radix Encoding. IEEE Trans. Neural Networks Learn. Syst. 35(3): 3689-3701 (2024) - [j5]Xiaozhe Gu, Zixun Zhang, Yuncheng Jiang, Tao Luo, Ruimao Zhang, Shuguang Cui, Zhen Li:
Hierarchical Weight Averaging for Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12276-12287 (2024) - [c8]Xiaozhe Gu, Ran Jin, Mingliang Li:
Progressively Relaxed Knowledge Distillation. IJCNN 2024: 1-8 - 2023
- [j4]Tian Huang, Jun Xu, Tao Luo, Xiaozhe Gu, Rick Siow Mong Goh, Weng-Fai Wong:
Benchmarking Quantum(-Inspired) Annealing Hardware on Practical Use Cases. IEEE Trans. Computers 72(6): 1692-1705 (2023) - [i9]Xiaozhe Gu, Zixun Zhang, Yuncheng Jiang, Tao Luo, Ruimao Zhang, Shuguang Cui, Zhen Li:
Hierarchical Weight Averaging for Deep Neural Networks. CoRR abs/2304.11519 (2023) - 2022
- [j3]Daniel Gerlinghoff, Zhehui Wang, Xiaozhe Gu, Rick Siow Mong Goh, Tao Luo:
E3NE: An End-to-End Framework for Accelerating Spiking Neural Networks With Emerging Neural Encoding on FPGAs. IEEE Trans. Parallel Distributed Syst. 33(11): 3207-3219 (2022) - [c7]Daniel Gerlinghoff, Zhehui Wang, Xiaozhe Gu, Rick Siow Mong Goh, Tao Luo:
A Resource-efficient Spiking Neural Network Accelerator Supporting Emerging Neural Encoding. DATE 2022: 92-95 - [c6]Xiaozhe Gu, Zixun Zhang, Tao Luo:
Temperature Annealing Knowledge Distillation from Averaged Teacher. ICDCS Workshops 2022: 133-138 - [i8]Tian Huang, Jun Xu, Tao Luo, Xiaozhe Gu, Rick Siow Mong Goh, Weng-Fai Wong:
Benchmarking Quantum(-inspired) Annealing Hardware on Practical Use Cases. CoRR abs/2203.02325 (2022) - [i7]Daniel Gerlinghoff, Zhehui Wang, Xiaozhe Gu, Rick Siow Mong Goh, Tao Luo:
A Resource-efficient Spiking Neural Network Accelerator Supporting Emerging Neural Encoding. CoRR abs/2206.02495 (2022) - 2021
- [i6]Zhehui Wang, Xiaozhe Gu, Rick Siow Mong Goh, Joey Tianyi Zhou, Tao Luo:
Efficient Spiking Neural Networks with Radix Encoding. CoRR abs/2105.06943 (2021) - [i5]Daniel Gerlinghoff, Zhehui Wang, Xiaozhe Gu, Rick Siow Mong Goh, Tao Luo:
E3NE: An End-to-End Framework for Accelerating Spiking Neural Networks with Emerging Neural Encoding on FPGAs. CoRR abs/2111.10027 (2021) - 2020
- [i4]Xiaozhe Gu, Arvind Easwaran:
Efficient Schedulability Test for Dynamic-Priority Scheduling of Mixed-Criticality Real-Time Systems. CoRR abs/2003.05160 (2020) - [i3]Xiaozhe Gu, Arvind Easwaran:
Dynamic Budget Management with Service Guarantees for Mixed-Criticality Systems. CoRR abs/2003.08364 (2020) - [i2]Xiaozhe Gu, Arvind Easwaran, Kieu-My Phan, Insik Shin:
Resource Efficient Isolation Mechanisms in Mixed-Criticality Scheduling. CoRR abs/2004.02400 (2020)
2010 – 2019
- 2019
- [j2]Xiaozhe Gu, Arvind Easwaran:
Dynamic budget management and budget reclamation for mixed-criticality systems. Real Time Syst. 55(3): 552-597 (2019) - [c5]Xiaozhe Gu, Arvind Easwaran:
Towards safe machine learning for CPS: infer uncertainty from training data. ICCPS 2019: 249-258 - [i1]Xiaozhe Gu, Arvind Easwaran:
Towards Safe Machine Learning for CPS: Infer Uncertainty from Training Data. CoRR abs/1909.04886 (2019) - 2018
- [b1]Xiaozhe Gu:
Schedulability analysis and low-criticality execution support for mixed-criticality real-time systems on uniprocessors. Nanyang Technological University, Singapore, 2018 - [j1]Xiaozhe Gu, Arvind Easwaran:
Efficient Schedulability Test for Dynamic-Priority Scheduling of Mixed-Criticality Real-Time Systems. ACM Trans. Embed. Comput. Syst. 17(1): 24:1-24:24 (2018) - [c4]Xiaozhe Gu, Arvind Easwaran, Risat Pathan:
Design and Analysis for Dual Priority Scheduling. ISORC 2018: 164-173 - 2016
- [c3]Xiaozhe Gu, Arvind Easwaran:
Dynamic Budget Management with Service Guarantees for Mixed-Criticality Systems. RTSS 2016: 47-56 - 2015
- [c2]Xiaozhe Gu, Arvind Easwaran, Kieu-My Phan, Insik Shin:
Resource Efficient Isolation Mechanisms in Mixed-Criticality Scheduling. ECRTS 2015: 13-24 - 2014
- [c1]Jaewoo Lee, Kieu-My Phan, Xiaozhe Gu, Jiyeon Lee, Arvind Easwaran, Insik Shin, Insup Lee:
MC-Fluid: Fluid Model-Based Mixed-Criticality Scheduling on Multiprocessors. RTSS 2014: 41-52
Coauthor Index
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