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Efficient Bitwidth Search for Practical Mixed Precision Neural Network., , , , , и . CoRR, (2020)Mimose: An Input-Aware Checkpointing Planner for Efficient Training on GPU., , , , , , , , , и 1 other автор(ы). CoRR, (2022)Incorporating Convolution Designs into Visual Transformers., , , , , и . ICCV, стр. 559-568. IEEE, (2021)Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models., , , , , , , и . CoRR, (2022)Once Quantization-Aware Training: High Performance Extremely Low-bit Architecture Search., , , , , , , , и . ICCV, стр. 5320-5329. IEEE, (2021)Extremely Low-bit Convolution Optimization for Quantized Neural Network on Modern Computer Architectures., , , , , , , , , и 1 other автор(ы). ICPP, стр. 38:1-38:12. ACM, (2020)BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction., , , , , , , , и . ICLR, OpenReview.net, (2021)SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency., , , , , , , , , и 1 other автор(ы). CoRR, (2023)QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization., , , , и . CoRR, (2022)NNLQP: A Multi-Platform Neural Network Latency Query and Prediction System with An Evolving Database., , , , и . ICPP, стр. 78:1-78:14. ACM, (2022)