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AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization., , , , , , , , и . MICRO, стр. 628-640. ACM, (2023)Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization., , , , , , , и . ICCAD, стр. 1-9. IEEE, (2021)Binary Complex Neural Network Acceleration on FPGA., , , , , , , , , и 2 other автор(ы). CoRR, (2021)RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference., , , , , , , , , и 4 other автор(ы). CoRR, (2023)Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate., , , , и . CoRR, (2024)Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search., , , , , , , , , и 2 other автор(ы). CoRR, (2021)Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads., , , , , , и . CoRR, (2024)Accommodating Transformer onto FPGA: Coupling the Balanced Model Compression and FPGA-Implementation Optimization., , , , , и . ACM Great Lakes Symposium on VLSI, стр. 163-168. ACM, (2021)Advanced Large Language Model (LLM)-Driven Verilog Development: Enhancing Power, Performance, and Area Optimization in Code Synthesis., , , , , , , и . CoRR, (2023)MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training., , , , , , , , и . ASPLOS (2), стр. 683-698. ACM, (2024)