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Projects & Cooperations:

Research Projects


HyLAP (Start: September 2014)

One of the major challenges of learning predictive models for complex tasks is the right hyperparameter and model selection strategy, as state-of-the-art approaches such as grid-search and random sampling require many runs of the learning algorithm, and therefore are usually conducted on large compute clusters rather than resource-restricted platforms such as robots, cars or mobile phones for instance. Therefore, autonomous hyperparameter learning strategies that are able to take into account observations of past hyperparameter performances on related problems have to be developed, enabling learning systems to learn in a fraction of the time it takes today.
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Contact: Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme



iTalk2Learn (Start: November 2012)

iTalk2Learn wants to develop a platform for intelligent support that combines structured learning with exploratory learning activities. To do so cognitive models are applied, that represent the learning behavior of students in elementary education. The platform will enable learners to communicate and interact more naturally via state of the art touch and speech interfaces.
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Contact: Neelava Sengupta, Carlotta Schatten, Lars Schmidt-Thieme



REDUCTION - Reducing Environmental Footprint based on Multi-Modal Fleet management Systems for Eco-Routing and Driver Behaviour Adaptation (Start: September 2011)

REDUCTION focuses on advanced solutions that combine mechanical / measurement technologies with information and communication technologies (ICT) for the management of multi-modal fleets, in order to reduce their environmental footprint.
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Contact: Josif Grabocka, Lars Schmidt-Thieme

EFRE project: AcoGPR - Adaptive Contactless Ground Penetrating Radar (Start: Juni 2011)
The ISMLL researches on advanced supervised machine learning models in the context of urban planning and development. The analysis of data gathered from ground penetrating radars allows for exact positioning of supply lines. Jointly with the University of Braunschweig and Detectino GmbH, a local company from Hildesheim, a mobile radar vehicle will be constructed and tested in real application scenarios. [more]
Contact: Andre Busche, Lars Schmidt-Thieme

DFG project on Multirelational Factorization Models (Since April 2011)
Factorization models are machine learning models that predict quantities based on historical data, i.e., customer preferences, health risks, etc. Factorization models specifically address problems where interactions between objects should be predicted about which not many data are known. The ISMLL works on factorization models for several years now. [more]
Contact: Lars Schmidt-Thieme

RFID-Enhanced Museum for Interactive Experience (REMIX)
(since Sep. 2010)
Visitors to physical museums are often overwhelmed by the vast amount of information available in the space they are exploring, making it difficult to select personally interesting content. Personalization solutions can provide the required user-centered interactivity between the visitors and the museums. The aim of the REMIX project is to address this problem using recommender systems. [more]
Contact: Alexandros Nanopoulos, Rasoul Karimi


Master Online Intelligent Embedded Microsystems (IEMS) (since October 2007)
Within the "Master Online Intelligent Embedded Microsystems" (IEMS) offered by the University of Freiburg, we provide the module "Analytic Methods". The module deals with probability theory, statistics and differential equations.
Contact: Christoph Freudenthaler, Lars Schmidt-Thieme



Recently Completed Projects
Learning Recommender Systems for Online Shops(LEFOS) (ended on Feb. 2011)
The LEFOS project aims at integrating recommender system components like the ones known from Amazon ("Customers Who Bought This Item Also Bought") in line of business E-commerce shops... [more]
Contact: Artus Krohn-Grimberghe, Lars Schmidt-Thieme

Dynamic Personalization of Multimedia (MyMedia) (ended on Feb. 2011)
We are drowning in a sea of information overload. Television channels, books and music assault our senses with far too much content. The volume of content on the internet is literally exploding. Not only traditional media but millions of individual users are putting their own content on the web. The massive popularity of YouTube is just one example of this phenomenon. So, in this flood, how do you find content that matters to you? How do you discover multimedia information and entertainment in a way that suits you personally? Isn’t there an easier way? ... [more]
Contact: Zeno Gantner, Lars Schmidt-Thieme

See also Completed Research Projects and Past Industry Cooperation