92 citations · 156 across the 18 of their papers we have counts for
17 papers · 1 filter
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…
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…
Input-Dynamic Distributed Algorithms for Communication Networks
Klaus-Tycho Foerster, Janne H. Korhonen, Ami Paz +2
Consider a distributed task where the communication network is fixed but the local inputs given to the nodes of the distributed system may change over time. In this work, we explor…
Relaxed Scheduling for Scalable Belief Propagation
Vitaly Aksenov, Dan Alistarh, Janne H. Korhonen
The ability to leverage large-scale hardware parallelism has been one of the key enablers of the accelerated recent progress in machine learning. Consequently, there has been consi…