Abstract: Multiple kernel clustering (MKC) optimally utilizes a group of pre-specified base kernels to improve clustering performance. Among existing MKC algorithms, the recently proposed late fusion ...

§ Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, U.K. ∥ Laboratory of Molecular Simulation, Institut des Sciences et Ingénierie Chimiques, Valais, École ...

Mt-KaHyPar is a shared-memory algorithm for partitioning graphs and hypergraphs. The balanced (hyper)graph partitioning problem asks for a partition of the node set of a (hyper)graph into k disjoint ...

MaxCut is a key NP-hard combinatorial optimization problem. Quantum computing offers methods to solve such problems potentially better than classical counterparts, with the Quantum Approximate ...

Abstract: Augmented reality (AR) is one of the emerging use cases relying on ultra-reliable and low-latency communications (uRLLC). The AR service is composed of multiple dependent ...

For non-planar graphs, such solutions are computationally intractable," explained the researchers. The algorithm relies on the Kac-Ward formalism, a mathematical method that allows exact computation ...

Graph Neural Networks (GNNs) have gained considerable attention in recent years. Despite the surge in innovative GNN architecture designs, research heavily relies on the same 5-10 benchmark datasets ...

As the world becomes increasingly data-driven, the demand for accurate and efficient search technologies has never been higher. Traditional search engines, while powerful, often struggle to meet the ...

In the realm of database development, the need for efficient data retrieval has led to the evolution of indexing techniques. Traditional methods like basic tables have proven inadequate for handling ...

Generative Artificial Intelligence can be an important asset in the drug discovery process to meet the demand for novel medicines. This work outlines the optimization and fine-tuning steps of MedGAN, ...