暂无分享,去创建一个
[1] Nicholas D. Lane,et al. DeepEye: Resource Efficient Local Execution of Multiple Deep Vision Models using Wearable Commodity Hardware , 2017, MobiSys.
[2] Nicholas D. Lane,et al. Mic2Mic: using cycle-consistent generative adversarial networks to overcome microphone variability in speech systems , 2019, IPSN.
[3] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[4] Daniel Rueckert,et al. A generic framework for privacy preserving deep learning , 2018, ArXiv.
[5] Ian Goodfellow,et al. Deep Learning with Differential Privacy , 2016, CCS.
[6] Sam Ade Jacobs,et al. Communication Quantization for Data-Parallel Training of Deep Neural Networks , 2016, 2016 2nd Workshop on Machine Learning in HPC Environments (MLHPC).
[7] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[8] Indranil Gupta,et al. Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance , 2018, ICML.
[9] Yuanzhou Yang,et al. Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes , 2018, ArXiv.
[10] Roland Vollgraf,et al. Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms , 2017, ArXiv.
[11] Alexander Sergeev,et al. Horovod: fast and easy distributed deep learning in TensorFlow , 2018, ArXiv.
[12] Fengyuan Xu,et al. Occlumency: Privacy-preserving Remote Deep-learning Inference Using SGX , 2019, MobiCom.
[13] Hubert Eichner,et al. Towards Federated Learning at Scale: System Design , 2019, SysML.
[14] Sebastian Caldas,et al. LEAF: A Benchmark for Federated Settings , 2018, ArXiv.
[15] Blaise Agüera y Arcas,et al. Communication-Efficient Learning of Deep Networks from Decentralized Data , 2016, AISTATS.
[16] Cecilia Mascolo,et al. Accelerating Mobile Audio Sensing Algorithms through On-Chip GPU Offloading , 2017, MobiSys.
[17] Sarvar Patel,et al. Practical Secure Aggregation for Privacy-Preserving Machine Learning , 2017, IACR Cryptol. ePrint Arch..
[18] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[19] Quoc V. Le,et al. Self-Training With Noisy Student Improves ImageNet Classification , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Ben Y. Zhao,et al. Latent Backdoor Attacks on Deep Neural Networks , 2019, CCS.
[21] Prateek Mittal,et al. Analyzing Federated Learning through an Adversarial Lens , 2018, ICML.
[22] Anit Kumar Sahu,et al. Federated Optimization in Heterogeneous Networks , 2018, MLSys.
[23] Marc'Aurelio Ranzato,et al. Large Scale Distributed Deep Networks , 2012, NIPS.
[24] Shwetak N. Patel,et al. Heterogeneous Bitwidth Binarization in Convolutional Neural Networks , 2018, NeurIPS.
[25] Lin Zhong,et al. RedEye: Analog ConvNet Image Sensor Architecture for Continuous Mobile Vision , 2016, 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA).
[26] Tian Li,et al. Fair Resource Allocation in Federated Learning , 2019, ICLR.