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 ...

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 ...

The VMamba (Visual State Space Model) is built upon the Mamba model by stacking Visual State Space (VSS) modules and utilizing the 2D Selective Scan (SS2D) module to extend the original Mamba model’s ...

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 ...

One of the key components of Microsoft’s Copilot Runtime edge AI development platform for Windows is a new vector search technology, DiskANN (Disk Accelerated Nearest Neighbors). Building on a ...

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 ...

Modeling in heterogeneous catalysis requires the extensive evaluation of the energy of molecules adsorbed on surfaces. This is done via density functional theory but for large organic molecules it ...