Domain Knowledge in Machine Learning Models for Sustainability with Stefano Ermon
EPISODE 15
|
MARCH
17,
2017
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About this Episode
My guest this week is Stefano Ermon, Assistant Professor of Computer Science at Stanford University, and Fellow at Stanford's Woods Institute for the Environment. Stefano and I met at the Re-Work Deep Learning Summit earlier this year, where he gave a presentation on Machine Learning for Sustainability.
Stefano and I spoke about a wide range of topics, including the relationship between fundamental and applied machine learning research, incorporating domain knowledge in machine learning models, dimensionality reduction, semi-supervised learning, proxy & transfer learning, and his interest in applying ML & AI to addressing sustainability issues such as poverty, food security and the environment.
About the Guest
Stefano Ermon
Stanford University
Resources
- Project: Combining Satellite Imagery and Machine Learning to Predict Poverty
- Paper: Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data
- Paper: Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping
- Paper: Combining Satellite Imagery and Machine Learning to Predict Poverty
- NASA MODIS Data Set
- Paper: Supervising Neural Networks with Physics and other Domain Knowledge | Code
