GitHub stars, while a vanity metric, influence project selection and investment decisions, leading to a market where stars are bought and sold; this article examines star pricing, common fraud patterns, and how unsupervised clustering and specialized tools can identify and mitigate fake-star activity.
This talk presents the application of voice analysis in financial risk control, covering voice‑based risk feature extraction, single‑channel speech separation techniques, and speech‑text labeling methods, demonstrating how acoustic and textual cues can be leveraged to improve risk detection and model performance.
This presentation explains how leveraging user behavior sequences with supervised and unsupervised deep learning models, including end‑to‑end and two‑stage architectures, improves transaction fraud detection by identifying distinct patterns of account takeover and stolen‑card activities and outlines the engineering deployment pipeline.
Gaode’s network positioning has evolved from unsupervised clustering of massive AP fingerprints and Bayesian grid ranking to a supervised two‑level hierarchical model that scores candidate grids with a neural‑network LTR loss, while adding scenario‑specific CNN and spatio‑temporal modules for indoor, rail and subway accuracy, and it now looks toward image‑based, 5G and IoT positioning.
