We would like to invite you to Scalable Algorithms for Semi-supervised and Unsupervised Learning.
Unsupervised and semi-supervised learning technologies such as hashing, sketching, clustering, graph-based learning, and graph algorithms, are the core of many fundamental applications at Google as well as important areas of research in academia. In all such real applications, the scalability of the algorithms and their efficiency for big data are central concerns. In this virtual workshop, we would like to bridge the gap between academic research and research at Google by bringing together researchers from both worlds. The workshop will allow Googlers and academics to present their research in these areas with a special focus on scalable algorithms. We plan to have both formal talks by experts of the field as well as opportunities to interact in poster sessions and break-out sessions. We expect to cover interdisciplinary areas such as high-performance graph computations, scalable GNNs, ML systems and optimization, and efficient unsupervised and semi supervised machine learning algorithms and infrastructure.
We hope this workshop will deepen the understanding of the unique and fascinating challenges of designing scalable algorithms for unsupervised and semi-supervised learning at Google, while enabling new connections between academics and Googlers.