Speaker: Frank HutterDate: 2022-05-05 Abstract Deep Learning (DL) has been able to revolutionize learning from raw data (images, text, speech, etc) by replacing domain-specific hand-crafted features with features that are jointly learned for the particular task at hand. I propose to take deep learning to the next level, by also Read more
Speaker: Arbër ZelaDate: 2022-04-15 Abstract Ensembles of neural networks achieve superior performance compared to standalone networks not only in terms of accuracy on in-distribution data but also on data with distributional shift alongside improved uncertainty calibration. Diversity among networks in an ensemble is believed to be key for building strong Read more
Speaker: Armin BiereDate: 2022-04-01 Abstract Armin Bieres research interests are applied formal methods, more specifically formal verification of hardware and software, using model checking and related techniques with the focus on developing efficient SAT and SMT solvers. He is the author and co-author of more than 220 papers and served Read more
Speaker: Abhinav ValadaDate: 2022-03-18 Abstract The research of the Robot Learning Lab lies at the intersection of robotics, machine learning and computer vision with a focus on tackling fundamental robot perception, state estimation and planning problems using learning approaches to enable robots to reliably operate in more complex domains and Read more
Speaker: André BiedenkappDate: 2022-08-26 Abstract The performance of many algorithms in the fields of hard combinatorial problem-solving, machine learning or AI in general depends on parameter tuning. Automated methods have been proposed to alleviate users from the tedious and error-prone task of manually searching for performance-optimized configurations. However, there is Read more