Microaggregation is a classical statistical disclosure control technique which requires the
input data to be partitioned into clusters while adhering to specified size constraints. We …

In spite of the fundamental role of neural networks in contemporary machine learning
research, our understanding of the computational complexity of optimally training neural …

Atomic congestion games are a classic topic in network design, routing, and algorithmic
game theory, and are capable of modeling congestion and flow optimization tasks in various …

We study the complexity-theoretic boundaries of tractability for three classical problems in
the context of Hierarchical Task Network Planning: the validation of a provided plan, whether …

Hypersphere classification is a classical and foundational method that can provide easy-to-
process explanations for the classification of real-valued as well as binary data. However …

We study the well-established problem of finding an optimal routing of unsplittable flows in a
graph. While by now there is an extensive body of work targeting the problem on graph …

Several works have recently investigated the parameterized complexity of data completion
problems, motivated by their applications in machine learning, and clustering in particular …