mlsanityData to 14 Oct 2026

Regularized Binary Network Training

arXiv 1812.11800 ↗First posted 31 Dec 2018cs.LG cs.CVcited by 14

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Abstract (arXiv)

There is a significant performance gap between Binary Neural Networks (BNNs) and floating point Deep Neural Networks (DNNs). We propose to improve the binary training method, by introducing a new regularization function that encourages training weights around binary values. In addition, we add trainable scaling factors to our regularization functions. Additionally, an improved approximation of the derivative of the sign activation function in the backward computation. These modifications are based on linear operations that are easily implementable into the binary training framework. Experimental results on ImageNet shows our method outperforms the traditional BNN method and XNOR-net.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Dec 2018.

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Citing papers per year: 2021: 4; 2022: 1; 2023: 4; 2024: 3; 2025: 2.

14 papers.

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  1. 2021A comprehensive review of Binary Neural Networkcited by 45
  2. 2021RA-BNN: Constructing Robust & Accurate Binary Neural Network to Simultaneously Defend Adversarial Bit-Flip Attack and Improve Accuracycited by 11
  3. 2023Efficient Neural Networks for Tiny Machine Learning: A Comprehensive Reviewcited by 9
  4. 2023On the Opportunities of Green Computing: A Surveycited by 7
  5. 2024Custom Gradient Estimators are Straight-Through Estimators in Disguisecited by 6
  6. 2024Understanding Neural Network Binarization with Forward and Backward Proximal Quantizerscited by 4
  7. 2021A Bop and Beyond: A Second Order Optimizer for Binarized Neural Networkscited by 3
  8. 2023Learning Label Encodings for Deep Regressioncited by 2
  9. 2021VC dimension of partially quantized neural networks in the overparametrized regimecited by 1
  10. 2022How to train accurate BNNs for embedded systems?cited by 1
  11. 2025Binary Neural Networks for Large Language Model: A Surveycited by 1
  12. 2023Quantization of Neural Network Equalizers in Optical Fiber Transmission Experimentscited by 0
2 more
  1. 2024A Fully Hardware Implemented Accelerator Design in ReRAM Analog Computing without ADCscited by 0
  2. 2025Cauchy-Schwarz Regularizerscited by 0