ASSET Seminar: “Copyright, Machine Learning Research, and the Generative-AI Supply Chain” (A. Feder Cooper, Cornell University)
ABSTRACT: “Does generative AI infringe copyright?” is an urgent question. It is also a difficult question, for two reasons. First, “generative AI” is not just one product from one company. […]
ASSET Seminar: “Towards a Design Flow for Verified AI-Based Autonomy” (Sajit A. Seshia, University of California, Berkeley)
ABSTRACT: Verified artificial intelligence (AI) is the goal of designing AI-based systems that have strong, ideally provable, assurances of correctness with respect to formally specified requirements. This talk will review […]
ASSET Seminar: “Lifelong Learning for Autonomous Systems: Progress and Challenges” (Eric Eaton, Penn)
ABSTRACT: Research in lifelong or continual machine learning has advanced rapidly over the past few years, primarily focusing on enabling learned models to acquire new tasks over time while avoiding […]
ASSET Seminar: “Towards Code-Aware Code Models” (Baishakhi Ray, Columbia University)
ABSTRACT: The past decade has seen unprecedented growth in Software Engineering— developers spend enormous time and effort to create new products. With such enormous growth comes the responsibility of producing […]
ASSET/IBI Symposium on Trustworthy AI for Health Care
Organizers: Rajeev Alur (Penn Engineering), John Holmes (PSOM), Insup Lee (Penn Engineering), Qi Long (PSOM), Marylyn Richie (PSOM) Event Description: Artificial intelligence and machine learning promise to revolutionize nearly every field, […]
ASSET Seminar: “Getting Computers to Do What We Want: Programming Meets Machine Learning” (Michael Littman, Brown University)
ABSTRACT: It is immensely empowering to delegate information processing and automation work to machines and have them carry out difficult tasks on our behalf. But programming computers is hard. The […]
ASSET Seminar: “Safety through Agility – Safe and Performant Control for Learning-Enabled Autonomous Systems” (Mangharam, Penn)
ABSTRACT: We present three approaches to combine formal methods, control theory, and machine learning for safe and performant autonomous systems. Safe control for learning-enabled systems: We present our recent progress […]
ASSET Seminar: “The Road to Explainable AI v2.0” (Eric Wong, Penn)
ABSTRACT: “A.I. has an explainability crisis”—Fortune Magazine. If you ask an ML researcher about explainability, you’ll find that there are a large number of interpretability methods with no clear consensus […]
ASSET Seminar: “Efficient and Targeted COVID-19 Border Testing Via Reinforcement Learning” (Hamsa Bastani, Penn)
ABSTRACT: Throughout the COVID-19 pandemic, countries relied on a variety of ad-hoc border control protocols to allow for non-essential travel while safeguarding public health: from quarantining all travellers to restricting […]