Present your research team of lab in a live video session and find partners for your international research cooperation at the upcoming virtual event of Meet My Lab x JFS.
The Southeast Asia-Europe Joint Funding Scheme for Research and Innovation (JFS) in cooperation with EURAXESS ASEAN is looking for researchers from Southeast Asia and Europe that are interested in presenting their laboratory at our Meet My Lab x JFS event. Deadline for application: 31 August 2021 at 23:59 CEST
August is Western Balkans Wiki Month! Our Chapter is organising a month-long action of creating and editing English Wikipedia articles related to science, technology, arts, and humanities in the Western Balkans region.
How can we trust systems built from machine learning components? We need advances in many areas, including machine learning algorithms, software engineering, ML ops, and explanation. This talk will describe our recent work in two important directions: obtaining calibrated performance estimates and performing run-time monitoring with guarantees. I will first describe recent work Jesse Hostetler on performance guarantees for reinforcement learning. Then I'll review our research on providing guarantees for open category detection and anomaly detection for run-time monitoring of deployed systems. I'll conclude with some speculations concerning meta-cognitive situational awareness for AI systems.
Dr. Dietterich (AB Oberlin College 1977; MS University of Illinois 1979; PhD Stanford University 1984) is Distinguished Professor Emeritus in the School of Electrical Engineering and Computer Science at Oregon State University. Dietterich is one of the pioneers of the field of Machine Learning and has authored more than 200 refereed publications and two books. His current research topics include robust artificial intelligence, robust human-AI systems, and applications in sustainability.
Link to the webinar (Webinar's virtual room will be accessible 15 minutes before the announced start):
https://rediris.zoom.us/j/8031759956?pwd=ZWdRZmtmUlhWSTlvNWYva0dNYm1qdz09
Meeting ID: 803 175 9956
Passcode: 0k7it5
