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ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design.

, , , , , , , , and . HPCA, page 273-286. IEEE, (2023)

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Max-Affine Spline Insights Into Deep Network Pruning., , , , , , , , and . Trans. Mach. Learn. Res., (2022)HALO: Hardware-Aware Learning to Optimize., , , , and . ECCV (9), volume 12354 of Lecture Notes in Computer Science, page 500-518. Springer, (2020)DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference., , , , , , and . CoRR, (2021)GEBT: Drawing Early-Bird Tickets in Graph Convolutional Network Training., , , and . CoRR, (2021)Introduction of Special Issue on Hardware and Algorithms for Efficient Machine Learning-Part 1., , and . ACM J. Emerg. Technol. Comput. Syst., 17 (2): 18:1-18:2 (2021)SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training., , , , , , , , and . CoRR, (2021)RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms., , , , , , , , and . CoRR, (2021)Towards Cognitive AI Systems: a Survey and Prospective on Neuro-Symbolic AI., , , , , , , , , and . CoRR, (2024)e-G2C: A 0.14-to-8.31 μJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM., , , , , , , , , and 3 other author(s). CoRR, (2022)Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference., , , , , and . AAAI, page 5700-5708. AAAI Press, (2020)