Stats, Optimization, and Machine Learning Seminar - Rose Yu
Rose Yu, College of Computer and Information Science, Northeastern University
Learning from Large-Scale Spatiotemporal Data
In many real-world applications, such as internet of things (IoT), transportation and physics, machine learning is applied to large-scale spatiotemporal data. Such data is often nonlinear, high-dimensional, and demonstrates complex spatial and temporal correlations. In this talk, I will demonstrate how to efficiently learn from such data. In particular, I will present some recent results on 1) Low-Rank Tensor Regression for spatiotemporal causal inference and 2) Diffusion Convolutional RNNs for spatiotemporal forecasting, applied to real-world traffic and climate data. I will also discuss opportunities and challenges of learning from large-scale spatiotemporal data.
Wednesday, September 19, 2018 at 3:00pm to 4:00pm
Engineering Center, ECOT 226
1111 Engineering Drive, Boulder, CO 80309