Fast Approximate Inference for Probabilistic Machine Learning in Complex Models
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Join us at the Applied Data Science Speak & Greet hosted by the University of Arizona Data Science Institute. The series will help to foster and promote building a network of researchers and graduate students, giving exposure to different interdisciplinary Data Science applications.
This month's featured speaker is Jason Pacheco, Assistant Professor in the Department of Computer Science at the University of Arizona. His research is in statistical machine learning which aims to build intelligent systems for automated reasoning in stochastic systems. Pacheco completed his PhD in Computer Science at Brown University and held a postdoc position at the MIT Sensing, Learning, and Inference Group.
Pacheco will discuss "Fast Approximate Inference for Probabilistic Machine Learning in Complex Models" and the use of probabilistic approaches to machine learning, inference, and sequential decision making when observable quantities provide only partial noisy information.
Please come to listen and learn. Then stay to chat with Jason Pacheco and Nirav Merchant, Director of the Data Science Institute.