This paper proposes a preprocessing framework for optimizing large-scale graph database ingestion through intelligent edge filtering based on value ranking. We combine adapted PageRank algorithms with ...
Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
Abstract: In this article, we study a multirobot stochastic patrolling problem by employing graph partitioning techniques, where each robot adopts a Markov-chain-based strategy over its assigned ...
⚡️ 72× faster than PTv3 for end-to-end semantic segmentation ⚡️ 5.3x faster than SPT for end-to-end semantic segmentation Simply run install.sh to install all dependencies in a new conda environment ...
Drug discovery is a challenging process with a huge molecular space to be explored and numerous pharmacological properties to be appropriately considered. Among various drug design protocols, fragment ...
Deciding whether two graphs are structurally identical, or isomorphic, is a classical algorithmic problem that has been studied since the early days of computing. Applications span a broad field of ...
A professionally curated list of awesome resources (paper, code, data, etc.) on Deep Graph Anomaly Detection (DGAD), which is the first work to comprehensively and systematically summarize the recent ...
Abstract: Balanced Graph Partitioning is one of the fundamental combinatorial optimization problems. It is still a challenge to effectively achieve a High-quality Balanced Graph Partitioning for super ...
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