Zobrazeno 1 - 10
of 1 157
pro vyhledávání: '"Gionis, A."'
Data summarization tasks are often modeled as $k$-clustering problems, where the goal is to choose $k$ data points, called cluster centers, that best represent the dataset by minimizing a clustering objective. A popular objective is to minimize the m
Externí odkaz:
http://arxiv.org/abs/2410.12913
We introduce Polaris, a network null model for colored multi-graphs that preserves the Joint Color Matrix. Polaris is specifically designed for studying network polarization, where vertices belong to a side in a debate or a partisan group, represente
Externí odkaz:
http://arxiv.org/abs/2409.01363
Providing recommendations that are both relevant and diverse is a key consideration of modern recommender systems. Optimizing both of these measures presents a fundamental trade-off, as higher diversity typically comes at the cost of relevance, resul
Externí odkaz:
http://arxiv.org/abs/2408.03772
Finding dense subnetworks, with density based on edges or more complex structures, such as subgraphs or $k$-cliques, is a fundamental algorithmic problem with many applications. While the problem has been studied extensively in static networks, much
Externí odkaz:
http://arxiv.org/abs/2406.10608
Today, as increasingly complex predictive models are developed, simple rule sets remain a crucial tool to obtain interpretable predictions and drive high-stakes decision making. However, a single rule set provides a partial representation of a learni
Externí odkaz:
http://arxiv.org/abs/2406.03059
Timeline algorithms are key parts of online social networks, but during recent years they have been blamed for increasing polarization and disagreement in our society. Opinion-dynamics models have been used to study a variety of phenomena in online s
Externí odkaz:
http://arxiv.org/abs/2402.10053
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 type of relationship between users, such as friends, family, or acquaint
Externí odkaz:
http://arxiv.org/abs/2402.09124
In this work, we study diversity-aware clustering problems where the data points are associated with multiple attributes resulting in intersecting groups. A clustering solution need to ensure that a minimum number of cluster centers are chosen from e
Externí odkaz:
http://arxiv.org/abs/2401.05502
Social media have great potential for enabling public discourse on important societal issues. However, adverse effects, such as polarization and echo chambers, greatly impact the benefits of social media and call for algorithms that mitigate these ef
Externí odkaz:
http://arxiv.org/abs/2308.14486
One of the most fundamental tasks in data science is to assist a user with unknown preferences in finding high-utility tuples within a large database. To accurately elicit the unknown user preferences, a widely-adopted way is by asking the user to co
Externí odkaz:
http://arxiv.org/abs/2307.02946