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 ...
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 ...
GriNNder trains full-graph GNNs on graphs whose activations/gradients exceed GPU memory by coordinating GPU memory, host RAM, and NVMe storage. The active open-source surface focuses on OGBN/IGB ...
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 ...
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 ...
Density peaks clustering algorithm (DP) has difficulty in clustering large-scale data, because it requires the distance matrix to compute the density and -distance for each object, which has time ...
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 ...
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Bayesian Decision Trees provide a probabilistic framework that reduces the instability of Decision Trees while maintaining their explainability. While Markov Chain Monte Carlo methods are typically ...
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