In recent years, significant advances have been made in the design and evaluation of
balanced (hyper) graph partitioning algorithms. We survey trends of the past decade in …

Hypergraphs are a generalization of graphs where edges (aka nets) are allowed to connect
more than two vertices. They have a similarly wide range of applications as graphs. This …

The increasing complexity of modern Integrated Circuits (ICs) leads to systems composed of
various different Intellectual Property (IPs) blocks, known as System-on-Chip (SoC). Such …

This chapter reviews applications of Memetic Algorithms in the areas of business analytics
and data science. This approach originates from the need to address optimization problems …

We present a refinement framework for multilevel hypergraph partitioning that uses max-flow
computations on pairs of blocks to improve the solution quality of ak-way partition. The …

State-of-the-art hypergraph partitioners follow the multilevel paradigm that constructs
multiple levels of progressively coarser hypergraphs that are used to drive cut refinement on …

The time complexity of support vector machines (SVMs) prohibits training on huge datasets
with millions of data points. Recently, multilevel approaches to train SVMs have been …

A directed acyclic hypergraph is a generalized concept of a directed acyclic graph, where
each hyperedge can contain an arbitrary number of tails and heads. Directed hypergraphs …

Problems in scientific computing, such as distributing large sparse matrix operations, have
analogous formulations as hypergraph partitioning problems. A hypergraph is a …

Balanced hypergraph partitioning is a classic NP-hard optimization problem that is a
fundamental tool in such diverse disciplines as VLSI circuit design, route planning, sharding …