484 citations
- University of HelsinkiFI46 papers
- Aalto UniversityFI37 papers
- Helsinki Institute of PhysicsFI4 papers
- KTH Royal Institute of TechnologySE4 papers
- University of ManchesterGB3 papers
- Hong Kong University of Science and TechnologyHK2 papers
- KU LeuvenBE2 papers
- Laboratoire d'Informatique, de Modélisation et d'Optimisation des SystèmesFR2 papers
- Tampere UniversityFI2 papers
- Technical University of MunichDE2 papers
- The University of OsakaJP2 papers
- University of FreiburgDE2 papers
97 papers
Point & Grasp: Flexible Selection of Out-of-Reach Objects Through Probabilistic Cue Integration
Xuejing Luo, Hee-Seung Moon, Christian Holz +1
Selecting out-of-reach objects is a fundamental task in mixed reality (MR). Existing methods rely on a single cue or deterministically fuse multiple cues, leading to performance de…
Adaptive Prompt Elicitation for Text-to-Image Generation
Xinyi Wen, Lena Hegemann, Xiaofu Jin +2
Aligning text-to-image generation with user intent remains challenging, as users frequently provide ambiguous inputs and struggle with model idiosyncrasies. We propose Adaptive Pro…
Compressed Dictionary Matching on Run-Length Encoded Strings
Philip Bille, Inge Li Gørtz, Simon J. Puglisi +1
Given a set of pattern strings and a text string , the classic dictionary matching problem is to report all occurrences of each pattern in…
Fair Diversity Maximization with Few Representatives
Florian Adriaens, Nikolaj Tatti
Diversity maximization problem is a well-studied problem where the goal is to find diverse items. Fair diversity maximization aims to select a diverse subset of items from…
Max-Min Diversification with Asymmetric Distances
Iiro Kumpulainen, Florian Adriaens, Nikolaj Tatti
One of the most well-known and simplest models for diversity maximization is the Max-Min Diversification (MMD) model, which has been extensively studied in the data mining and data…
Dense Subgraph Discovery Meets Strong Triadic Closure
Chamalee Wickrama Arachchi, Iiro Kumpulainen, Nikolaj Tatti
Finding dense subgraphs is a core problem with numerous graph mining applications such as community detection in social networks and anomaly detection. However, in many real-world…