83 citations · 346 across the 78 of their papers we have counts for
7 papers · 1 filter
Survey of Generative Methods for Social Media Analysis
Stan Matwin, Aristides Milios, Paweł Prałat +2
This survey draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the research in generative methods for the analysis of social media data. It fills a void, as…
A Multi-purposed Unsupervised Framework for Comparing Embeddings of Undirected and Directed Graphs
Bogumił Kamiński, Łukasz Kraiński, Paweł Prałat +1
Graph embedding is a transformation of nodes of a network into a set of vectors. A good embedding should capture the underlying graph topology and structure, node-to-node relations…
Perfect Matchings in the Semi-random Graph Process
Pu Gao, Calum MacRury, Pawel Pralat
The semi-random graph process is a single player game in which the player is initially presented an empty graph on vertices. In each round, a vertex is presented to the pla…
Subgraph Games in the Semi-Random Graph Process and Its Generalization to Hypergraphs
Natalie C. Behague, Trent G. Marbach, Pawel Pralat +1
The semi-random graph process is a single-player game that begins with an empty graph on vertices. In each round, a vertex is presented to the player independently and unif…
Makespan Trade-offs for Visiting Triangle Edges
Konstantinos Georgiou, Somnath Kundu, Pawel Pralat
We study a primitive vehicle routing-type problem in which a fleet of unit speed robots start from a point within a non-obtuse triangle , where . The goal is…
Localization Game for Random Geometric Graphs
Lyuben Lichev, Dieter Mitsche, Pawel Pralat
The localization game is a two player combinatorial game played on a graph . The cops choose a set of vertices with . The robber then chooses a…
Evaluating Node Embeddings of Complex Networks
Arash Dehghan-Kooshkghazi, Bogumił Kamiński, Łukasz Kraiński +2
Graph embedding is a transformation of nodes of a graph into a set of vectors. A~good embedding should capture the graph topology, node-to-node relationship, and other relevant inf…