神经网络基础:感知机、多层网络、训练方法、CNN图像分类
Perceptrons
Multi-layer Networks
Training Method
Best Practices
CNN
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现代预训练模型:Transformer架构、BERT预训练与微调、扩展模型
Transformer
Learning/Data
BERT
Fine-Tuning
Extensions
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对抗攻击与防御:白盒/黑盒攻击、模型反演、模型抽取
Understanding
Evasion
White-box
Black-box
Model Inversion
Model Extraction
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模型蒸馏与抽取:知识迁移、模型窃取、攻击与防御
Understanding
Model Distillation
Model Extraction
Attack Methods
Defense
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后门攻击与防御:数据投毒、模型投毒、Neural Cleanse检测
Backdoor Taxonomy
Outsourcing
BadNets
Trojaning
Federated Learning
Defense
Neural Cleanse
开始学习
隐私保护:成员推断、属性推断、差分隐私
Threats
Privacy Risks
Membership Inference
Attribute Inference
Differential Privacy
开始学习
深度伪造与检测:人脸合成、换脸技术、伪造检测、泛化性
Generation
Face Synthesis
Attribute Manipulation
Face Swap
Detection
Datasets
Generalizability
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