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DataFunSummit
DataFunSummit
Apr 16, 2024 · Artificial Intelligence

Intelligent Risk Control: Definitions, Expert Systems, Algorithmic Systems, and Emerging AI Techniques

This article explains intelligent risk control as a synergy of expert experience and algorithmic decision‑making, outlines its definition, expert human systems, digital algorithmic systems, and explores advanced AI methods such as reinforcement learning, large language models with knowledge graphs, adversarial learning, graph neural networks, and a practical supply‑chain case study.

Graph Neural NetworkKnowledge Graphadversarial learning
0 likes · 11 min read
Intelligent Risk Control: Definitions, Expert Systems, Algorithmic Systems, and Emerging AI Techniques
DataFunSummit
DataFunSummit
Mar 23, 2024 · Artificial Intelligence

Graph Neural Networks for Real-World Complex Scenarios

This article presents a comprehensive overview of recent graph neural network research, covering adversarial representation learning for network embedding, block‑model guided GCN, enhanced class‑discriminative GNNs, self‑supervised contrastive GNNs, experimental results, and conclusions, highlighting their significance in real‑world applications.

GCNadversarial learninggraph neural networks
0 likes · 13 min read
Graph Neural Networks for Real-World Complex Scenarios
AntTech
AntTech
May 10, 2023 · Artificial Intelligence

Brainwave and Behavior Recognition: Multi‑Modal Biometric Authentication with Adversarial Contrastive Transfer Learning

This article presents Ant Security's research on novel biometric methods—brainwave (脑纹) and behavior recognition—detailing their scientific background, data collection, multi‑modal deep‑learning algorithms, adversarial and contrastive training strategies, experimental results, and practical applications for inclusive, secure identity verification.

Multimodal AIaccessibilityadversarial learning
0 likes · 17 min read
Brainwave and Behavior Recognition: Multi‑Modal Biometric Authentication with Adversarial Contrastive Transfer Learning
AntTech
AntTech
Mar 31, 2022 · Artificial Intelligence

Trustworthy AI in the Digital Economy: Practices and Explorations by Ant Group

In a keynote at the Machine Heart AI Technology Conference, Ant Group's Zhou Jun presented the concept of trustworthy AI, detailing its integration with privacy, security, graph learning, explainable and adversarial machine learning, and large‑scale privacy‑preserving techniques to enhance financial risk control in the digital economy.

Explainable Machine LearningPrivacy-Preserving MLadversarial learning
0 likes · 20 min read
Trustworthy AI in the Digital Economy: Practices and Explorations by Ant Group
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 21, 2019 · Artificial Intelligence

How View-Specific Information Boosts Multi-View Multi-Label Learning (SIMM)

This article explains the SIMM algorithm, a multi‑view multi‑label learning method that extracts view‑specific information alongside shared subspace representations, detailing its motivation, architecture, loss functions, experimental results on eight datasets, and how it outperforms existing approaches.

SIMMadversarial learningmulti-label classification
0 likes · 10 min read
How View-Specific Information Boosts Multi-View Multi-Label Learning (SIMM)
Youku Technology
Youku Technology
Aug 12, 2019 · Artificial Intelligence

Interpretation of the Paper “Multi-View Multi-Label Learning with View‑Specific Information Extraction” (SIMM)

The article explains SIMM, a neural‑network framework for multi‑view multi‑label learning that jointly extracts a shared, view‑invariant subspace via adversarial loss and orthogonal view‑specific features, demonstrating superior performance across eight benchmark datasets compared to existing MVML and ML‑kNN methods.

AIadversarial learningmachine learning
0 likes · 11 min read
Interpretation of the Paper “Multi-View Multi-Label Learning with View‑Specific Information Extraction” (SIMM)
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 1, 2019 · Artificial Intelligence

How Alibaba’s Knowledge Engine Advances AI with Adversarial NER and Graph Embedding

This article reviews Alibaba’s year‑long Knowledge Engine program, detailing its five‑module architecture, major technical breakthroughs such as automatic ontology building and deep‑learning alignment, and two flagship research works: adversarial learning for crowdsourced NER and an iterative rule‑and‑embedding reasoning framework.

AIKnowledge Graphadversarial learning
0 likes · 9 min read
How Alibaba’s Knowledge Engine Advances AI with Adversarial NER and Graph Embedding