The next meeting of the Montreal Computational and Qualitative Linguistics Lab will take place on Wednesday April 1st, at 1:00, via Zoom (meeting ID: 912 324 021). This week, Guillaume Rabusseau will present on “Spectral Learning of Weighted Automata and Connections with Recurrent Neural Networks and Tensor Networks”.
Structured objects such as strings, trees, and graphs are ubiquitous in data science but learning functions defined over such objects can be a tedious task. Weighted finite automata~(WFAs) and recurrent neural networks~(RNNs) are two powerful and flexible classes of models which can efficiently represent such functions.In this talk, Guillaume will introduce WFAs and the spectral learning algorithm before presenting surprising connections between WFAs, tensor networks and recurrent neural networks. Guillaume Rabusseau is an assistant professor at Univeristé de Montréal and at the Mila research institute since Fall 2018, and a Canada CIFAR AI (CCAI) chair holder since March 2019.  His research interests lie at the intersection of theoretical computer science and machine learning, and his work revolves around exploring inter-connections between tensors and machine learning and developing efficient learning methods for structured data relying on linear and multilinear algebra.
Meeting ID: 912 324 021