Find a story
Search Spins
Search titles, summaries, and missing voices across published articles — press releases, announcements, and media coverage.
3 results for “directed acyclic graph”
PPO-STGNN: A Proximal Policy Optimization Approach with Spatio-Temporal Graph Neural Networks for DAG Task Scheduling in Cloud-Edge-End Computing
A new reinforcement learning algorithm called PPO-STGNN is proposed to improve scheduling of computation-intensive DAG tasks across cloud, edge, and end devices by jointly modeling task dependencies and heterogeneous infrastructure using spatio-temporal graph neural networks and proximal policy optimization.
Sep 4, 2026
HubSpot Redesigns JITA Authorization with Rule Engine Architecture
HubSpot replaced its legacy conditional authorization logic with a new rule engine architecture for Just-In-Time Access (JITA), enabling structured decision metadata, rule-level observability, and governance workflows.
Aug 3, 2026
How Does Bayesian Causal Discovery Fail? Characterising Structural Consequences in Linear Gaussian Networks under Latent Confounding
A new arXiv preprint identifies and characterizes two distinct failure regimes of Bayesian causal discovery methods when applied to linear Gaussian models with additive latent confounding between exactly two observed variables, showing that increasing sample size lowers the correlation threshold at which spurious edges are favoured.
Jul 13, 2026