reference.md

## Reference

[1]. Jakub Konečný, H. Brendan McMahan, Daniel Ramage, Peter Richtárik. **Federated Optimization: Distributed Machine Learning for On-Device Intelligence.** 2016

[2]. H. Brendan McMahan, Eider Moore, Daniel Ramage, Blaise Agüera y Arcas. **Federated Learning of Deep Networks using Model Averaging.** 2017

[3]. Jakub Konečný, H. Brendan McMahan, Felix X. Yu, Peter Richtárik, Ananda Theertha Suresh, Dave Bacon. **Federated Learning: Strategies for Improving Communication Efficiency.** 2016

[4]. Qiang Yang, Yang Liu, Tianjian Chen, Yongxin Tong. **Federated Machine Learning: Concept and Applications.** 2019

[5]. Kai He, Liu Yang, Jue Hong, Jinghua Jiang, Jieming Wu, Xu Dong et al. **PrivC  - A framework for efficient Secure Two-Party Computation.** In Proc. of SecureComm 2019

[6]. Martín Abadi, Andy Chu, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang. **Deep Learning with Differential Privacy.** 2016

[7]. Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi, Ameet Talwalkar. **Federated Multi-Task Learning** 2016

[8]. Yang Liu, Tianjian Chen, Qiang Yang. **Secure Federated Transfer Learning.** 2018

[9]. Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikk. **Session-based Recommendations with Recurrent Neural Networks.** 2016

[10]. https://en.wikipedia.org/wiki/Secret_sharing

[11]. Payman Mohassel and Peter Rindal. **ABY3: A Mixed Protocol Framework for Machine Learning.** In Proc. of CCS 2018