This lecture overviews Wireless Communication Networks that has many applications in autonomous systems. It covers the following topics in detail: 4G networks, Quality of Service in 4G networks, 5G networks, 5G technology components, Quality of Service in 5G networks, Internet of Things (IoT).
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Federated Learning
This lecture overviews that has many applications in distributed Machine Learning and privacy protection. It covers the following topics in detail: Centralized/Decentralized Learning, Federated Learning principles and platforms, Federated Learning Algorithms (Federated Averaging Algorithm, FedProx algorithm, FedMA algorithm) and Privacy Principles & Technologies, notably: Differential Privacy, Homomorphic Encryption, Zero-knowledge Proof Technologies, Secure Multiparty Computation.
Transfer Learning
This lecture overviews Transfer Learning (TL) that has many applications in DNN training and adaptation, Image Understanding, Text Mining, Activity Recognition, Bioinformatics, Transportation. It covers the following topics in detail: Definition of TL, Categorization of TL: Instance-based (Noninductive, Inductive), Feature-based, Model-based, Relation-based, Heterogeneous TL, Negative Transfer, TL with Deep Learning, Fundamental TL Research Issues, Applications of TL.
Domain Adaptation
This lecture overviews Domain Adaptation that has many applications in DNN training and adaptation. It covers the following topics in detail: Domain Shift, Unsupervised Domain Adaptation (Domain-specific Whitening Transform, Min-entropy Consensus loss, Maximum Classification Discrepancy, Sliced Wasserstein Discrepancy), Deep Learning methods for Unsupervised Domain Adaptation ( DLID: Deep learning for DA by Interpolating between Domains),… Continue reading Domain Adaptation
Continual Learning
This lecture overviews Continual Learning that has many applications in DNN training and adaptation. It covers the following topics in detail: catastrophic forgetting, Regularization CL Methods EWC model), Dynamic CL Approaches (DEN model), Complementary architectures (Fearnet model).
Explainable AI
This lecture overviews Explainable AI that has many applications in trustworthy AI systems and autonomous systems. It covers the following topics in detail: Interpretability, Interpretability Types (Visual explanations, Image-based Plot visualizations, Textual explanations, Numerical-Mathematical explanations), Explainable AI Applications and Frameworks.