ICMCS 2016 - Workshop on Reliable Machine Learning in the Wild

How can we be confident that a system that performed well in the past will do so in the future, in the presence of novel and potentially adversarial input distributions? Answering these questions is critical for high stakes applications such as autonomous driving, as well as for building reliable large-scale machine learning systems. This workshop explores approaches that are principled or can provide performance guarantees, ensuring AI systems are robust and beneficial in the long run. We will focus on three aspects ? robustness, adaptation, and monitoring ? that can aid us in designing and deploying reliable machine learning systems.