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$A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks., , , , , , , and . ICLR, OpenReview.net, (2023)Efficient Accelerator/Network Co-Search With Circular Greedy Reinforcement Learning., , and . IEEE Trans. Circuits Syst. II Express Briefs, 70 (7): 2615-2619 (July 2023)MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization., , , , , , , and . HPCA, page 124-138. IEEE, (2024)Block Convolution: Toward Memory-Efficient Inference of Large-Scale CNNs on FPGA., , , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 41 (5): 1436-1447 (2022)Block Convolution: Towards Memory-Efficient Inference of Large-Scale CNNs on FPGA., , , and . CoRR, (2021)Hardware Acceleration of CNN with One-Hot Quantization of Weights and Activations., , , , and . DATE, page 971-974. IEEE, (2020)EBERT: Efficient BERT Inference with Dynamic Structured Pruning., , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 4814-4823. Association for Computational Linguistics, (2021)A2Q: Aggregation-Aware Quantization for Graph Neural Networks., , , , , , , and . CoRR, (2023)MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization., , , , , , , and . CoRR, (2023)TBERT: Dynamic BERT Inference with Top-k Based Predictors., , and . DATE, page 1-6. IEEE, (2023)