Speaker: Josif GrabockaDate: 2022-09-23 Josif Grabocka from the Representation Learning Research Group at Uni Freiburg will give a talk titled “Efficient Hyperparameter Optimization in the Age of Deep Learning“. Abstract Hyperparameter Optimization (HPO) is essential in designing state-of-the-art Machine Learning systems. Unfortunately, existing HPO techniques are not efficient enough for Read more…
Speaker: Daniel HonerkampDate: 2022-08-26 Abstract Mobile manipulation remains a critical challenge across both service and industrial settings and is a key component to visions such as household assistants. But for this it requires the combination of a wide range of capabilities, such as perception and exploration in unknown environments while Read more…
Speaker: Chenguang HuangDate: 2022-08-12 Abstract Robot navigation has been an actively researched challenge for decades. With different focuses, navigation goals can be defined in many different ways such as goal images, relative positions, semantic objects, and sound sources. Recently, with the advances in both computer vision and natural language processing Read more…
Speaker: Adam KortylewskiDate: 2022-07-29 Abstract Deep learning sparked a tremendous increase in the performance of computer vision systems over the past decade. However, Deep Neural Networks (DNNs) are still far from reaching human-level performance at visual recognition tasks. The most important limitation of DNNs is that they fail to give Read more…
Speaker: Jens KoberDate: 2022-06-24 Abstract The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. I will discuss various learning techniques we developed that enable robots to have complex interactions with their environment and humans. Complexity arises from dealing with high-dimensional input data, non-linear Read more…
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…