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[45]
M. Wang, I. McInerney, B. Stellato, S. Boyd, and H. K.-H. So

RSQP: Problem-Specific Architectural Customization for Accelerated Convex Quadratic Optimization,” in Proceedings of the 50th Annual International Symposium on Computer Architecture, ser. ISCA ’23, Orlando, FL, USA: Association for Computing Machinery, 2023.

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X. Hou, J. Liu, X. Tang, et al.

Architecting Efficient Multi-Modal AIoT Systems,” in Proceedings of the 50th Annual International Symposium on Computer Architecture, ser. ISCA ’23, Orlando, FL, USA: Association for Computing Machinery, 2023.

[43]
S. Jiang, T.-W. Huang, B. Yu, and T.-Y. Ho

SNICIT: Accelerating Sparse Neural Network Inference via Compression at Inference Time on GPU,” in Proceedings of the 52nd International Conference on Parallel Processing, ser. ICPP ’23, Salt Lake City, UT, USA: Association for Computing Machinery, 2023, pp. 51–61.

[42]
T. Ergen, H. I. Gulluk, J. Lacotte, and M. Pilanci

Globally Optimal Training of Neural Networks with Threshold Activation Functions,” in The Eleventh International Conference on Learning Representations, 2023.

[41]
Y. Wang and M. Pilanci

Sketching the Krylov subspace: faster computation of the entire ridge regularization path,” The Journal of Supercomputing, vol. 79, no. 16, pp. 18 748–18 776, May 2023.

[40]
C. Tao and N. Wong

ODG-Q: Robust Quantization via Online Domain Generalization,” in 2022 26th International Conference on Pattern Recognition (ICPR), 2022, pp. 1822–1828.

[39]
L. Chen, X. Li, and J. Xu

Improve the Stability and Robustness of Power Management through Model-free Deep Reinforcement Learning,” in 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2022, pp. 1371–1376.

[38]
Y. Liu, J. Zhang, J. Feng, S. Chen, and J. Xu

A Reliability Concern on Photonic Neural Networks,” in 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2022, pp. 1059–1064.

[37]
Z. Guan, W. Zhou, Y. Ren, R. Xie, H. Yu, and N. Wong

A Hardware-Aware Neural Architecture Search Pareto Front Exploration for In-Memory Computing,” in 2022 IEEE 16th International Conference on Solid-State & Integrated Circuit Technology (ICSICT), 2022, pp. 1–4.

[36]
A.-N. Xiong, Y.-F. Fan, S.-Q. Dai, C. Xu, J. G. Yuan, and M. Chan

A CMOS Compatible In-sensor Computing Neural Network with Gate/Body-Tied PMOSFET Array,” in 2022 IEEE 16th International Conference on Solid-State & Integrated Circuit Technology (ICSICT), 2022, pp. 1–3.

[35]
X. Wang, X. Liu, X. Hu, et al.

TAC-RAM: A 65nm 4Kb SRAM Computing-in-Memory Design with 57.55 TOPS/W supporting Multibit Matrix-Vector Multiplication for Binarized Neural Network,” in 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2022, pp. 66–69.

[34]
X. Li, L. Chen, S. Chen, F. Jiang, C. Li, and J. Xu

Power Management for Chiplet-Based Multicore Systems Using Deep Reinforcement Learning,” in 2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2022, pp. 164–169.

[33]
J. Feng, S. Chen, J. Zhang, Y. Fu, and J. Xu

Energy-Efficient High-Performance Photonic Backplane Network for Rack-Scale Computing Systems,” in 2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2022, pp. 122–127.

[32]
R. Wang and W.-N. Lee

A General Deep Learning Model for Ultrasound Localization Microscopy,” in 2022 IEEE International Ultrasonics Symposium (IUS), 2022, pp. 1–4.

[31]
S. Lin and M. D. Wong

“Superfast Full-Scale GPU-Accelerated Global Routing,” in 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2022, pp. 1–8.

[30]
C. Li, F. Jiang, S. Chen, et al.

“Accelerating Cache Coherence in Manycore Processor through Silicon Photonic Chiplet,” in 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2022, pp. 1–9.

[29]
Z. Liu, K.-T. Cheng, D. Huang, E. Xing, and Z. Shen

Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation,” in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Los Alamitos, CA, USA: IEEE Computer Society, Jun. 2022, pp. 4932–4942.

[28]
Z. Xiao, V. B. Naik, S. K. Cheung, et al.

Device Variation-Aware Adaptive Quantization for MRAM- based Accurate In-Memory Computing Without On-chip Training,” in 2022 International Electron Devices Meeting (IEDM), 2022, pp. 10.5.1–10.5.4.

[27]
M. Jiang, K. Shan, X. Sheng, C. Graves, J. P. Strachan, and C. Li

An efficient synchronous-updating memristor-based Ising solver for combinatorial optimization,” in 2022 International Electron Devices Meeting (IEDM), 2022, pp. 22.2.1–22.2.4.

[26]
Y. Li, W. Zhang, X. Xu, et al.

Mixed-Precision Continual Learning Based on Computational Resistance Random Access Memory,” Advanced Intelligent Systems, vol. 4, no. 8, p. 2 200 026, 2022.