Upcoming Events
MOVED TO ZOOM Evaluating the Robustness and Efficiency of Estimators for Informative Covariate Censoring
Abstract: While right-censored time-to-event outcomes have been studied for decades, handling time-to-event covariates, also known as censored covariates, is now of growing interest. So far,…
EVENT CANCELED Who’s Afraid of AI? Myths and Realities of Generative AI
Abstract: There has been a spike in concern about existential risk from artificial general intelligence, or AGI. This fear, commonly associated with terms such as…
Specifying Goals to Deep Neural Networks with Answer Set Programming
Abstract: Methods such as DeepCubeA have used deep reinforcement learning to learn domain-specific heuristic functions in a largely domain-independent fashion to solve planning problems. However,…
(Virtual) – (Nearly) 40 Years of SE+AI
Abstract: Dr. Kaiser will discuss her past work applying AI-based techniques to software engineering problems and applying software engineering techniques to finding bugs in AI…
Learning Latent Graphs from Stationary Signals
Abstract: Graphs and networks are widely used to represent complex systems such as genetic regulatory networks, brain connectivity networks, etc. Learning underlying graphs from high-dimensional…