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Title: Systems problems in deep learning Abstract: Advances in deep learning are enabling novel applications like autonomous vehicles and advanced medical imaging. But despite the overwhelming promise of deep learning, ML engineers still struggle with performing basic tasks like distributing training, running hyperparameter searches, and reproducing experiment results. This is likely due to the fact […]
We have 3 exciting invited talks from industry in my graduate CSE course titled "Data Systems for Machine Learning" (coursewebpage). The topics span ML deployment platforms, deep learning training platforms, and GPU acceleration for data science workloads. I'd like to open up these talks to the wider CSE and HDSI talks audiences. The full 3-talk […]
For the final Database Seminar of this quarter on Friday (Dec 4) at 3pm PT, we have another exciting external speaker, Alex Ratner. He is going to tell us about programmatic approaches to label data for modern ML/AI applications that reduce the burden of manual hand labeling. Please find the talk details and Zoom details […]
Talk Contents How to apply AI Tech to Education? Introduction of Riiid Labs & Technology Future of AI-enabled Education $100K Riiid! AIEd Challenge on Kaggle Date/Time January 13 (Wed), 5:00PM-6:00PM Open to all members of HDSI Community Prerequisite: Intellectual curiosity to explore the future of education with AI Get More Info riiid.co ednetchallenge.ai kaggle.com/c/riiid-test-answer-prediction aaai.org/Conferences/AAAI-21 […]
Talk title: "Data Science at Disney"Emily Kubicek, Ph.D.Bio:Hi there My name is Emily Kubicek and I'm a Data Scientist at The Walt Disney Company. I am San Diego born and raised, have two dogs named Nani and Loki, and now live in Los Angeles. I graduated from San José State University with a BA in Communication Sciences […]
Title: A modern take on Huber regression Abstract: In the first part of the talk, we discuss the use of a penalized Huber M-estimator for high-dimensional linear regression. We explain how a fairly straightforward analysis yields high-probability error bounds that hold even when the additive errors are heavy-tailed. However, the parameter governing the shape of […]
Title: Causal Effect Inference: A Machine Learning Approach Abstract A major challenge in the domain of healthcare is ascertaining whether a given treatment influences or determines an outcome—for instance, whether there is a survival benefit to prescribing a certain medication. Current treatment guidelines have been developed with the “average” patient in mind, but the reality […]