1. Martín Abadi Paul Barham Jianmin Chen Zhifeng Chen Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Geoffrey Irving Michael Isard Manjunath Kudlur Josh Levenberg Rajat Monga Sherry Moore Derek G. Murray Benoit Steiner Paul Tucker Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2016. TensorFlow: a system for Large-Scale machine learning (OSDI'16). https://www.usenix.org/conference/osdi16/technical-sessions/presentation/abadi Martín Abadi Paul Barham Jianmin Chen Zhifeng Chen Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Geoffrey Irving Michael Isard Manjunath Kudlur Josh Levenberg Rajat Monga Sherry Moore Derek G. Murray Benoit Steiner Paul Tucker Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2016. TensorFlow: a system for Large-Scale machine learning (OSDI'16). https://www.usenix.org/conference/osdi16/technical-sessions/presentation/abadi
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3. Dan Alistarh Torsten Hoefler Mikael Johansson Sarit Khirirat Nikola Konstantinov and Cédric Renggli. 2018. The Convergence of Sparsified Gradient Methods (NIPS'18). https://proceedings.neurips.cc/paper_files/paper/2018/file/314450613369e0ee72d0da7f6fee773c-Paper.pdf Dan Alistarh Torsten Hoefler Mikael Johansson Sarit Khirirat Nikola Konstantinov and Cédric Renggli. 2018. The Convergence of Sparsified Gradient Methods (NIPS'18). https://proceedings.neurips.cc/paper_files/paper/2018/file/314450613369e0ee72d0da7f6fee773c-Paper.pdf
4. Batiste Le Bars Aurélien Bellet Marc Tommasi Erick Lavoie and Anne-Marie Kermarrec. 2023. Refined Convergence and Topology Learning for Decentralized Optimization with Heterogeneous Data (AISTATS'23). arXiv:2204.04452 Batiste Le Bars Aurélien Bellet Marc Tommasi Erick Lavoie and Anne-Marie Kermarrec. 2023. Refined Convergence and Topology Learning for Decentralized Optimization with Heterogeneous Data (AISTATS'23). arXiv:2204.04452
5. Aurélien Bellet Anne-Marie Kermarrec and Erick Lavoie. 2022. D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learning (SRDS'22). Aurélien Bellet Anne-Marie Kermarrec and Erick Lavoie. 2022. D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learning (SRDS'22).