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10 events found.
Guest Lecture
Jeffrey L. Elman Distinguished Lecture Series: The Decision-Making Side of Machine Learning: Computational, Inferential and Economic Perspectives
Title: The Decision-Making Side of Machine Learning: Computational, Inferential and Economic Perspectives Abstract: Much of the recent focus in machine learning has been on the pattern-recognition side of the field. I will focus instead on the decision-making side, where many fundamental challenges remain. Some are statistical in nature, including the challenges associated with multiple decision-making, […]
Data Science Insights Speaker Series: Yian Ma
Details Exploration Problem in Sequential Decision Making: A Computational Perspective by Yian Ma Abstract: Efficient Exploration is often the bottleneck for solving sequential decision making problems. Many different approaches have been proposed and analyzed, such as explore-then-commit, upper confidence bound, etc. Much of the focus has been on using frequentist perspectives to understand and develop […]
Data Science Insights Speaker Series: Arya Mazumdar
In partnership with the San Diego Machine Learning Meetup Group, we are excited to be launching this monthly speaker series. The intent for this series is to highlight faculty and data science related research from the Institute and UC San Diego to the broader community. Our next monthly event will be taking place on Wednesday, […]
Data Science and Biology – Speaker Series
Data Science and Biology - Speaker Series Hosted by Diversity in Data Science & CELLebrate Event Description Data Science and Biology - Speaker Series provides an exciting opportunity to hear from experienced professionals about various data science techniques with applications to the biological sciences. All undergraduate/graduate students, faculty, and staff interested in STEM are […]
Towards the Statistically Principled Design of ML Algorithms | Frederic Koehler
SDSC, The Auditorium 9836 Hopkins Dr, La Jolla, San Diego, CA, United StatesWhat are the optimal algorithms for learning from data? Have we found them already, or are better ones out there to be discovered? Making these questions precise, and answering them, requires taking on the mathematically deep interplay between statistical and computational constraints. It also requires reconciling our theoretical toolbox with surprising new phenomena arising from practice, which seem to violate conventional rules of thumb regarding algorithm and model design. I will discuss progress along these lines: in terms of designing new algorithms for basic learning problems, controlling generalization in large statistical models, and understanding key statistical questions for generative modeling.
Intelligent mobile systems for equitable healthcare
SDSC, The Auditorium 9836 Hopkins Dr, La Jolla, San Diego, CA, United StatesAccess to even basic medical resources is greatly influenced by factors like an individual's birth country and zip code. In this talk, I will present my work on designing AI-based mobile systems for equitable healthcare. I will showcase three systems that are not only interesting from an AI standpoint but are also having real-world medical impact. The first system can detect ear infections using only a smartphone and a paper cone. The second system enables low-cost newborn hearing screening using inexpensive earphones. Lastly, I will present an ambient sensing system that employs smart devices to detect emergent and life-threatening medical events such as cardiac arrest. Through these examples, I will demonstrate how new applied machine learning and sensing approaches that generalize across hardware and work in real-world environments can help to address pressing societal problems.
The Interplay of Technology, Ethics, and Policy
Public Engagement Building (PEB) 721 9625 Scholars Drive North MC 0305, La Jolla, CA, United StatesAbstract: Technology is often designed and deployed without critical reflection of the values that it embodies. Value trade-offs—between security and privacy, free speech and dignity, autonomy and human agency, and different conceptions of fairness—abound in many technologies that are now achieving great scale in commonly used tech platforms. The decisions made by the people inside […]