ProxyBNN: Learning Binarized Neural Networks via Proxy Matrices

[1]  Diana Marculescu,et al.  Regularizing Activation Distribution for Training Binarized Deep Networks , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  Christoph Meinel,et al.  Back to Simplicity: How to Train Accurate BNNs from Scratch? , 2019, ArXiv.

[3]  Ethan Fetaya,et al.  Learning Discrete Weights Using the Local Reparameterization Trick , 2017, ICLR.

[4]  Nikos Komodakis,et al.  Wide Residual Networks , 2016, BMVC.

[5]  Mehrdad Yazdani,et al.  Linear Backprop in non-linear networks , 2018 .

[6]  Alexander G. Anderson,et al.  The High-Dimensional Geometry of Binary Neural Networks , 2017, ICLR.

[7]  Ran El-Yaniv,et al.  Binarized Neural Networks , 2016, ArXiv.

[8]  Eddy Mayoraz,et al.  Constructive Training Methods for feedforward Neural Networks with Binary weights , 1995, Int. J. Neural Syst..

[9]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[10]  Xiangyu He,et al.  BitStream , 2018, Proceedings of the 26th ACM international conference on Multimedia.

[11]  Natalia Gimelshein,et al.  PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.

[12]  Max Welling,et al.  Probabilistic Binary Neural Networks , 2018, ArXiv.

[13]  Wei Liu,et al.  Bi-Real Net: Enhancing the Performance of 1-bit CNNs With Improved Representational Capability and Advanced Training Algorithm , 2018, ECCV.

[14]  Yu Qiao,et al.  A Discriminative Feature Learning Approach for Deep Face Recognition , 2016, ECCV.

[15]  Jian Cheng,et al.  Sparsity-Inducing Binarized Neural Networks , 2020, AAAI.

[16]  IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks , 2019, ArXiv.

[17]  D. Haussler,et al.  Boolean Feature Discovery in Empirical Learning , 1990, Machine Learning.

[18]  Yoshua Bengio,et al.  Neural Networks with Few Multiplications , 2015, ICLR.

[19]  Chuanyi Ji,et al.  Capacity of Two-Layer Feedforward Neural Networks with Binary Weights , 1998, IEEE Trans. Inf. Theory.

[20]  Gang Hua,et al.  How to Train a Compact Binary Neural Network with High Accuracy? , 2017, AAAI.

[21]  Luca Benini,et al.  XNORBIN: A 95 TOp/s/W hardware accelerator for binary convolutional neural networks , 2018, 2018 IEEE Symposium in Low-Power and High-Speed Chips (COOL CHIPS).

[22]  Houqiang Li,et al.  Quantization Networks , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[23]  Jing Hu,et al.  BitStream: Efficient Computing Architecture for Real-Time Low-Power Inference of Binary Neural Networks on CPUs , 2018, ACM Multimedia.

[24]  Rongrong Ji,et al.  Bayesian Optimized 1-Bit CNNs , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[25]  Shuchang Zhou,et al.  DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients , 2016, ArXiv.

[26]  Guodong Guo,et al.  Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs , 2019, IJCAI.

[27]  Wei Pan,et al.  Towards Accurate Binary Convolutional Neural Network , 2017, NIPS.

[28]  Aleksander Madry,et al.  How Does Batch Normalization Help Optimization? (No, It Is Not About Internal Covariate Shift) , 2018, NeurIPS.

[29]  Alberto L. Sangiovanni-Vincentelli,et al.  Learning Complex Boolean Functions: Algorithms and Applications , 1993, NIPS.

[30]  P. Schönemann,et al.  A generalized solution of the orthogonal procrustes problem , 1966 .

[31]  Gary R. Bradski,et al.  ORB: An efficient alternative to SIFT or SURF , 2011, 2011 International Conference on Computer Vision.

[32]  Peisong Wang,et al.  K-Nearest Neighbors Hashing , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[33]  Shenghuo Zhu,et al.  Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM , 2017, AAAI.

[34]  Yoshua Bengio,et al.  BinaryConnect: Training Deep Neural Networks with binary weights during propagations , 2015, NIPS.

[35]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[36]  David S. Doermann,et al.  Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation , 2018, AAAI.

[37]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[38]  Hanqing Lu,et al.  Fast and Accurate Image Matching with Cascade Hashing for 3D Reconstruction , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[39]  Eriko Nurvitadhi,et al.  WRPN: Wide Reduced-Precision Networks , 2017, ICLR.

[40]  Svetlana Lazebnik,et al.  Iterative quantization: A procrustean approach to learning binary codes , 2011, CVPR 2011.

[41]  Ali Farhadi,et al.  XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks , 2016, ECCV.

[42]  G. Guo,et al.  GBCNs: Genetic Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs , 2019, AAAI Conference on Artificial Intelligence.

[43]  Alexandr Andoni,et al.  Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions , 2006, 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06).

[44]  Kwang-Ting Cheng,et al.  Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization , 2019, NeurIPS.

[45]  Jingkuan Song,et al.  Forward and Backward Information Retention for Accurate Binary Neural Networks , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[46]  Jian Cheng,et al.  From Hashing to CNNs: Training BinaryWeight Networks via Hashing , 2018, AAAI.

[47]  Maja Pantic,et al.  Improved training of binary networks for human pose estimation and image recognition , 2019, ArXiv.

[48]  Ron Meir,et al.  Mean Field Bayes Backpropagation: scalable training of multilayer neural networks with binary weights , 2013 .

[49]  Mouloud Belbahri,et al.  BNN+: Improved Binary Network Training , 2018, ArXiv.

[50]  Yifan Zhang,et al.  Fast K-means for Large Scale Clustering , 2017, CIKM.

[51]  Georgios Tzimiropoulos,et al.  XNOR-Net++: Improved binary neural networks , 2019, BMVC.

[52]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[53]  Georgios Tzimiropoulos,et al.  Training Binary Neural Networks with Real-to-Binary Convolutions , 2020, ICLR.

[54]  Ron Meir,et al.  Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights , 2014, NIPS.