1 citations · 3 across the 19 of their papers we have counts for
23 papers
Parallel Algorithms for Higher-Order Temporal H-Index Computation
Lutz Oettershagen
Ranking vertices by importance is a fundamental task in network mining. The H-index provides such a ranking by asking how many neighbors are themselves well connected; its higher-o…
Fair Top-k Katz Centrality via Graph Design
Ivan Qin, Prudence Wong, Lutz Oettershagen
Centrality measures are widely used to rank nodes in networked data, but fairness interventions for graph centrality typically target global score mass or modify the centrality ope…
Unsupervised Multi-Scale Gromov-Wasserstein Hypergraph Alignment
Lutz Oettershagen, Honglian Wang, Aristides Gionis
We study unsupervised hypergraph alignment, where the goal is to infer node correspondences between two hypergraphs using only structural information, without node features, labels…
Linguistic Monoculture in LLM-Assisted Language Use
Suhas Thejaswi, Juhi Kulshreshta, Lutz Oettershagen
Writing and communication are increasingly mediated by large language models (LLMs) that are being used to draft, revise and polish text. Although such assistance can improve clari…
Query-Limited Community Recovery in Stochastic Block Models
Sabyasachi Basu, Manuj Mukherjee, Lutz Oettershagen +1
We study exact community recovery in the two-community stochastic block model on vertices under limited and noisy access to network data. The learner may query a noisy neighbor…
Efficient Banzhaf-Based Data Valuation for -Nearest Neighbors Classification
Guangyi Zhang, Lutz Oettershagen, Lixu Wang +1
Data valuation, the task of quantifying the contribution of individual data points to model performance, has emerged as a fundamental challenge in machine learning. Game-theoretic…
Top-k on a Budget: Adaptive Ranking with Weak and Strong Oracles
Lutz Oettershagen
Identifying the top- items is fundamental but often prohibitive when exact valuations are expensive. We study a two-oracle setting with a fast, noisy weak oracle and a scarce, h…
Streaming Stochastic Submodular Maximization with On-Demand User Requests
Honglian Wang, Sijing Tu, Lutz Oettershagen +1
We explore a novel problem in streaming submodular maximization, inspired by the dynamics of news-recommendation platforms. We consider a setting where users can visit a news websi…
Fair Minimum Labeling: Efficient Temporal Network Activations for Reachability and Equity
Lutz Oettershagen, Othon Michail
Balancing resource efficiency and fairness is critical in networked systems that support modern learning applications. We introduce the \emph{Fair Minimum Labeling} (FML) problem:…
Consistent Tie-Strength Labeling for Multilayer Strong Triadic Closure
Lutz Oettershagen, Athanasios L. Konstantinidis, Fariba Ranjbar +1
Inferring tie strengths (strong vs. weak) is a core task in network analysis, often guided by the Strong Triadic Closure (STC) principle. In multilayer networks, such as social pla…
Finding Densest Subgraphs with Edge-Color Constraints
Lutz Oettershagen, Honglian Wang, Aristides Gionis
We consider a variant of the densest subgraph problem in networks with single or multiple edge attributes. For example, in a social network, the edge attributes may describe the ty…
An Edge-Based Decomposition Framework for Temporal Networks
Lutz Oettershagen, Athanasios L. Konstantinidis, Giuseppe F. Italiano
A temporal network is a dynamic graph where every edge is assigned an integer time label that indicates at which discrete time step the edge is available. We consider the problem o…
A Higher-Order Temporal H-Index for Evolving Networks
Lutz Oettershagen, Nils M. Kriege, Petra Mutzel
The H-index of a node in a static network is the maximum value such that at least of its neighbors have a degree of at least . Recently, a generalized version, the -t…
A Temporal Graphlet Kernel for Classifying Dissemination in Evolving Networks
Lutz Oettershagen, Nils M. Kriege, Claude Jordan +1
We introduce the \emph{temporal graphlet kernel} for classifying dissemination processes in labeled temporal graphs. Such dissemination processes can be spreading (fake) news, infe…
TGLib: An Open-Source Library for Temporal Graph Analysis
Lutz Oettershagen, Petra Mutzel
We initiate an open-source library for the efficient analysis of temporal graphs. We consider one of the standard models of dynamic networks in which each edge has a discrete times…
Inferring Tie Strength in Temporal Networks
Lutz Oettershagen, Athanasios L. Konstantinidis, Giuseppe F. Italiano
Inferring tie strengths in social networks is an essential task in social network analysis. Common approaches classify the ties as wea} and strong ties based on the strong triadic…
Temporal Walk Centrality: Ranking Nodes in Evolving Networks
Lutz Oettershagen, Petra Mutzel, Nils M. Kriege
We propose the Temporal Walk Centrality, which quantifies the importance of a node by measuring its ability to obtain and distribute information in a temporal network. In contrast…
An Index for Single Source All Destinations Distance Queries in Temporal Graphs
Lutz Oettershagen, Petra Mutzel
Temporal closeness is a generalization of the classical closeness centrality measure for analyzing evolving networks. The temporal closeness of a vertex is defined as the sum o…
Spatio-Temporal Top-k Similarity Search for Trajectories in Graphs
Lutz Oettershagen, Anne Driemel, Petra Mutzel
We study the problem of finding the most similar trajectories to a given query trajectory. Our work is inspired by the work of Grossi et al. [6] that considers trajectories as…
Temporal Graph Kernels for Classifying Dissemination Processes
Lutz Oettershagen, Nils M. Kriege, Christopher Morris +1
Many real-world graphs or networks are temporal, e.g., in a social network persons only interact at specific points in time. This information directs dissemination processes on the…
On the Enumeration and Counting of Bicriteria Temporal Paths
Petra Mutzel, Lutz Oettershagen
We discuss the complexity of path enumeration and counting in weighted temporal graphs. In a weighted temporal graph, each edge has an availability time, a traversal time and some…
The Crossing Number of Semi-Pair-Shellable Drawings of Complete Graphs
Petra Mutzel, Lutz Oettershagen
The Harary-Hill Conjecture states that for every drawing of has at least \begin{align*} H(n) := \frac{1}{4}\Big\lfloor\frac{n}{2}\Big\rfloor\Big\lfloor\frac{n-1}{2}…
The Crossing Number of Seq-Shellable Drawings of Complete Graphs
Petra Mutzel, Lutz Oettershagen
The Harary-Hill conjecture states that for every the complete graph on vertices , the minimum number of crossings over all its possible drawings equals \begin{align*…