ASSET Seminar: Statistical and Machine Learning for Electronic Health Records: Challenges and Opportunities, Qi Long (University of Pennsylvania)
ABSTRACT: Electronic health records (EHRs) offer great promises in advancing clinical research and transforming learning health systems. However, complex, temporal EHRs are fraught with biases and present daunting analytical challenges […]
ASSET Seminar: ML for Causal Inference, Konrad Kording, University of Pennsylvania
ABSTRACT Machine learning traditionally does not get at causality and causality research traditionally treats machine learning as a dangerous set of highly biased estimators. In my talk I will talk […]
ASSET Seminar: AI and Medicine: One Possible Future for Augmented Care, Kevin B Johnson (University of Pennsylvania)
Abstract: Scientific discoveries, fueled by data collected during the course of care, are promising to radically change how we think about health, disease, prevention and treatment. However, the very systems […]
ASSET Seminar: Scallop: A Language for Neuro-Symbolic Programming, Mayur Naik (University of Pennsylvania)
ABSTRACT: Neurosymbolic learning is an emerging paradigm which, at its core, combines the otherwise complementary worlds of classical algorithms and deep learning; in doing so, it ushers in more accurate, […]
ASSET Seminar: Building Safe Autonomous Systems, Rahul Mangharam (University of Pennsylvania)
ABSTRACT: Balancing performance and safety are crucial to deploying autonomous vehicles in multi-agent environments. In particular, autonomous racing is a domain that penalizes safe but conservative policies, highlighting the need […]
ASSET Seminar: Decision-Aware Learning for Global Health Supply Chains, Osbert Bastani (University of Pennsylvania)
ABSTRACT: Machine learning algorithms are increasingly used in conjunction with optimization to guide decision making. A key challenge is aligning the machine learning loss with the decision-making loss. Existing solutions […]
ASSET Seminar: Building certifiably safe and correct large-scale autonomy, Chuchu Fan (Massachusetts Institute of Technology)
ABSTRACT: The introduction of machine learning (ML) and artificial intelligence (AI) creates unprecedented opportunities for achieving full autonomy. However, learning-based methods in building autonomous systems can be extremely brittle in […]
ASSET Seminar: How to Design Molecules that Dock Well but Can’t Exist, Jacob Gardner, Ph.D.
ABSTRACT:BIO Machine learning has become an indispensable aid to researchers developing the next generation of novel therapeutics. In this talk, I will discuss how some of the most important problems in […]
ASSET Seminar: New approaches to detecting and adapting to domain shifts in machine learning, Zico Kolter, Ph.D. (Carnegie Mellon University)
ABSTRACT: Machine learning systems, in virtually every deployed system, encounter data from a qualitatively different distribution than what they were trained upon. Effectively dealing with this problem, known as domain […]
ASSET Seminar: What Transfers in Transfer Learning?, Eric Wong (University of Pennsylvania)
Abstract: Recently, the transfer learning paradigm has seen a surge of interest due to its impressive capabilities in vision and language. Models are pretrained on ever-growing datasets with enormous parameter […]