CML-IOT 2020: the second workshop on continual and multimodal learning for internet of things

With the deployment of Internet of Things (IoT), large amount of sensors are connected into the Internet, providing large-amount, streaming, and multimodal data. These data have distinct statistical characteristics over time and sensing modalities, which are hardly captured by traditional learning methods. Continual and multimodal learning allows integration, adaptation, and generalization of the knowledge learned from experiential data collected with heterogeneity to new situations. Therefore, continual and multimodal learning is an important step to enable efficient ubiquitous computing on IoT devices. The major challenges to combine continual learning and multimodal learning with real-world data include 1) how to fuse and transfer knowledge between the multimodal data under constrained computational resources, 2) how to learn continually despite the missing, imbalanced or noisy data under constrained computational resources, 3) how to effectively reserve privacy and retain security when learning knowledge from streaming and multimodal data collected by multiple stakeholders, and 4) how to develop large-scale distributed learning systems to efficiently learn from continual and multimodal data. We organize this workshop to bring people working on different disciplines together to tackle these challenges in this topic. This workshop aims to explore the intersection and combination of continual machine learning and multimodal modeling with applications in the Internet of Things. The workshop welcomes works addressing these issues in different applications/domains as well as algorithmic and systematic approaches to leverage continual learning on multimodal data. We further seek to develop a community that systematically handles the streaming multimodal data widely available in real-world ubiquitous computing systems. In 2019, we held the First Workshop on Continual and Multimodal Learning for Internet of Things (https://cmliot2019.github.io/) with Ubicomp 2019, London, UK. The First workshop accepted 12 papers from 17 submissions. The one-day agenda included 3 sessions and attracted around 20 attendees from academia and industries to discuss and share visions.