9 citations · 10 across the 4 of their papers we have counts for
4 papers
Unlocking the Potential of Collaborative AI -- On the Socio-technical Challenges of Federated Machine Learning
Tobias Müller, Milena Zahn, Florian Matthes
The disruptive potential of AI systems roots in the emergence of big data. Yet, a significant portion is scattered and locked in data silos, leaving its potential untapped. Federat…
SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced Training
Philipp Altmann, Leo Sünkel, Jonas Stein +3
Applying new computing paradigms like quantum computing to the field of machine learning has recently gained attention. However, as high-dimensional real-world applications are not…
Towards Multi-Agent Reinforcement Learning using Quantum Boltzmann Machines
Tobias Müller, Christoph Roch, Kyrill Schmid +1
Reinforcement learning has driven impressive advances in machine learning. Simultaneously, quantum-enhanced machine learning algorithms using quantum annealing underlie heavy devel…
Solving Large Steiner Tree Problems in Graphs for Cost-Efficient Fiber-To-The-Home Network Expansion
Tobias Müller, Kyrill Schmid, Daniëlle Schuman +3
The expansion of Fiber-To-The-Home (FTTH) networks creates high costs due to expensive excavation procedures. Optimizing the planning process and minimizing the cost of the earth e…