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Binarized neural networks: Training deep neural networks with weights and activations constrained to+ 1 or-1

, , , , и . arXiv preprint arXiv:1602.02830, (2016)

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Itay Cnaan-On

 

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Accurate Post Training Quantization With Small Calibration Sets., , , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 4466-4475. PMLR, (2021)Binarized neural networks: Training deep neural networks with weights and activations constrained to+ 1 or-1, , , , и . arXiv preprint arXiv:1602.02830, (2016)Minimum Variance Unbiased N: M Sparsity for the Neural Gradients., , , и . ICLR, OpenReview.net, (2023)Binarized Neural Networks., , и . CoRR, (2016)Augment Your Batch: Improving Generalization Through Instance Repetition., , , , , и . CVPR, стр. 8126-8135. Computer Vision Foundation / IEEE, (2020)The Knowledge Within: Methods for Data-Free Model Compression., , , и . CVPR, стр. 8491-8499. Computer Vision Foundation / IEEE, (2020)Fix your classifier: the marginal value of training the last weight layer., , и . ICLR (Poster), OpenReview.net, (2018)Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators., , и . ICLR, OpenReview.net, (2024)Playing SNES in the Retro Learning Environment., , и . ICLR (Workshop), OpenReview.net, (2017)Train longer, generalize better: closing the generalization gap in large batch training of neural networks., , и . NIPS, стр. 1731-1741. (2017)