ACM SIGACCESS Conference on Computers and Accessibility是为残疾人和老年人提供与计算机相关的设计、评估、使用和教育研究的首要论坛。我们欢迎提交原始的高质量的有关计算和可访问性的主题。今年,ASSETS首次将其范围扩大到包括关于计算机无障碍教育相关主题的原创高质量研究。官网链接:


The broad application of artificial intelligence techniques ranging from self-driving vehicles to advanced medical diagnostics afford many benefits. Federated learning is a new breed of artificial intelligence, offering techniques to help bridge the gap between personal data protection and utilization for research and commercial deployment, especially in the use-cases where security and privacy are the key concerns. Here, we present OpenFed, an open-source software framework to simultaneously address the demands for data protection and utilization. In practice, OpenFed enables state-of-the-art model development in low-trust environments despite limited local data availability, which lays the groundwork for sustainable collaborative model development and commercial deployment by alleviating concerns of asset protection. In addition, OpenFed also provides an end-to-end toolkit to facilitate federated learning algorithm development as well as several benchmarks to fair performance comparison under diverse computing paradigms and configurations.