92 citations · 156 across the 18 of their papers we have counts for
23 papers
Low-Bandwidth Matrix Multiplication: Faster Algorithms and More General Forms of Sparsity
Chetan Gupta, Janne H. Korhonen, Jan Studený +2
In prior work, Gupta et al. (SPAA 2022) presented a distributed algorithm for multiplying sparse matrices, using computers. They assumed that the input matrices ar…
Demand-Aware Network Design with Steiner Nodes and a Connection to Virtual Network Embedding
Aleksander Figiel, Janne H. Korhonen, Neil Olver +1
Emerging optical and virtualization technologies enable the design of more flexible and demand-aware networked systems, in which resources can be optimized toward the actual worklo…
Sparse Matrix Multiplication in the Low-Bandwidth Model
Chetan Gupta, Juho Hirvonen, Janne H. Korhonen +2
We study matrix multiplication in the low-bandwidth model: There are computers, and we need to compute the product of two matrices. Initially computer knows ro…
Beyond Distributed Subgraph Detection: Induced Subgraphs, Multicolored Problems and Graph Parameters
Janne H. Korhonen, Amir Nikabadi
Subgraph detection has recently been one of the most studied problems in the CONGEST model of distributed computing. In this work, we study the distributed complexity of problems c…
Sinkless Orientation Made Simple
Alkida Balliu, Janne H. Korhonen, Fabian Kuhn +9
The sinkless orientation problem plays a key role in understanding the foundations of distributed computing. The problem can be used to separate two fundamental models of distribut…
Towards Tight Communication Lower Bounds for Distributed Optimisation
Dan Alistarh, Janne H. Korhonen
We consider a standard distributed optimisation setting where machines, each holding a -dimensional function , aim to jointly minimise the sum of the functions $\sum_{i…