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Pu-Learning

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Sohu Tech Products
Sohu Tech Products
Jun 7, 2023 · Artificial Intelligence

Multiscale PU Learning for Detecting AI‑Generated Text

Researchers from Peking University and Huawei present a multiscale positive‑unlabeled learning framework that significantly improves detection of AI‑generated short and long texts, addressing the difficulty of distinguishing AI‑written content from human writing and outperforming existing baselines on multiple benchmarks.

AI detectionPu-LearningText Classification
0 likes · 8 min read
Multiscale PU Learning for Detecting AI‑Generated Text
DataFunTalk
DataFunTalk
Apr 11, 2022 · Artificial Intelligence

Precise Marketing Algorithms and Practices at Hello Mobility

This article presents Hello Mobility's precise marketing system, detailing its business background, value, framework, algorithmic capabilities—including Pu‑Learning LookAlike modeling, semi‑supervised TSA, and graph‑embedding techniques—addressing challenges such as sparse features and low ROI, and sharing performance improvements and future directions.

Data EngineeringPrecise MarketingPu-Learning
0 likes · 14 min read
Precise Marketing Algorithms and Practices at Hello Mobility
AntTech
AntTech
Apr 24, 2018 · Artificial Intelligence

Anomaly Detection with Partially Observed Anomalies: A Two‑Stage Semi‑Supervised Approach

This article summarizes a two‑stage method for anomaly detection when only a few labeled anomalies and many unlabeled instances are available, detailing problem formulation, isolation‑forest‑based scoring, clustering of anomalies, weighted multiclass modeling, experimental validation, and real‑world URL attack applications.

Anomaly DetectionPu-LearningSemi-supervised Learning
0 likes · 10 min read
Anomaly Detection with Partially Observed Anomalies: A Two‑Stage Semi‑Supervised Approach
Ctrip Technology
Ctrip Technology
Sep 10, 2016 · Artificial Intelligence

Deep Learning Anti‑Scam Guide: An Informal Introduction to Neural Networks, Training, and Practical Applications

This article provides a light‑hearted yet thorough overview of deep learning, covering neural network fundamentals, layer construction, back‑propagation, ResNet shortcuts, encoder‑decoder structures, PU‑learning for unlabeled data, GPU acceleration, and practical advice on data size, frameworks, and deployment in financial scenarios.

Big DataGPUPu-Learning
0 likes · 27 min read
Deep Learning Anti‑Scam Guide: An Informal Introduction to Neural Networks, Training, and Practical Applications
Qunar Tech Salon
Qunar Tech Salon
Aug 19, 2016 · Artificial Intelligence

Deep Learning Anti‑Scam Guide: A Non‑Technical Overview of Neural Networks, Training, and Practical Tips

This article provides a humorous yet informative, non‑mathematical guide to deep learning, covering neural network basics, layer addition, training methods, back‑propagation, unsupervised pre‑training, regularization, ResNet shortcuts, GPU computation, framework choices, and practical advice for applying deep learning to industrial data.

AIGPUPu-Learning
0 likes · 26 min read
Deep Learning Anti‑Scam Guide: A Non‑Technical Overview of Neural Networks, Training, and Practical Tips