Privacy-Preserving Machine Learning Courses and Certifications

TheIACR

Privacy-Preserving Machine Learning Workshop 2023 - Contributed Talks Session II

Explore cutting-edge research in privacy-preserving machine learning through expert presentations at the PPML 2023 workshop, covering innovative techniques and applications in the field.

• YouTube
• 1 hour 50 minutes
• On-Demand
• Free Video

TheIACR

Privacy-Preserving Machine Learning - Invited and Contributed Talks

Explore privacy-preserving machine learning with expert Mariana Raykova and contributed talks from PPML 2023, covering cutting-edge research and advancements in secure AI and data protection.

• YouTube
• 1 hour 26 minutes
• On-Demand
• Free Video

TheIACR

Privacy-Preserving Machine Learning Workshop - Invited and Contributed Talks

Explore cutting-edge research in privacy-preserving machine learning with expert talks and contributions at PPML 2023, covering innovative techniques and advancements in the field.

• YouTube
• 1 hour 28 minutes
• On-Demand
• Free Video

TheIACR

Privacy-Preserving Machine Learning: Challenges and Opportunities - Invited Talk

Explore privacy-preserving machine learning with Sewoong Oh's invited talk at PPML 2023, covering cutting-edge techniques and advancements in protecting data privacy during ML processes.

• YouTube
• 47 minutes
• On-Demand
• Free Video

Toronto Machine Learning Series (TMLS)

Privacy Risks and Protections in Machine Learning Systems

Explore privacy vulnerabilities in ML systems and learn robust protection strategies to safeguard sensitive training data while maintaining system effectiveness and user trust.

• YouTube
• 37 minutes
• On-Demand
• Free Video

USENIX

OblivGNN: Oblivious Inference on Transductive and Inductive Graph Neural Networks

Discover a privacy-preserving solution for secure GNN inference in cloud services, enabling protected analysis of sensitive graph data while maintaining model confidentiality and efficiency.

• YouTube
• 13 minutes
• On-Demand
• Free Video

USENIX

MD-ML: Super Fast Privacy-Preserving Machine Learning for Malicious Security with Dishonest Majority

Explore groundbreaking advances in privacy-preserving machine learning with MD-ML framework, offering enhanced security and efficiency for multi-party computation in neural network inference and training.

• YouTube
• 12 minutes
• On-Demand
• Free Video

USENIX

Scalable Multi-Party Computation Protocols for Machine Learning in the Honest-Majority Setting

Discover groundbreaking advances in privacy-preserving machine learning through scalable multi-party computation protocols, featuring efficient methods for secure operations and unprecedented performance with up to 63 parties.

• YouTube
• 13 minutes
• On-Demand
• Free Video

USENIX

GAZELLE - A Low Latency Framework for Secure Neural Network Inference

Efficient framework for secure neural network inference combining homomorphic encryption and two-party computation, outperforming existing systems in speed while preserving privacy for cloud-based machine learning.

• YouTube
• 27 minutes
• On-Demand
• Conference Talk

USENIX

Privacy Budget Scheduling

Explores privacy budget scheduling in machine learning, introducing PrivateKube for managing differential privacy as a resource. Presents DPF algorithm for fair allocation of non-replenishable privacy budgets in ML workloads.

• YouTube
• 14 minutes
• On-Demand
• Conference Talk

RSA Conference

Protect Privacy in a Data-Driven World - Privacy-Preserving Machine Learning

Explore privacy-preserving machine learning techniques to harness AI's power while maintaining data confidentiality, with insights on federated learning, trusted execution environments, and homomorphic encryption.

• YouTube
• 47 minutes
• On-Demand
• Conference Talk

IEEE

Towards Practical Differentially Private Convex Optimization

Explore practical approaches to differentially private convex optimization, including a novel algorithm and extensive empirical evaluation across various datasets, advancing privacy-preserving machine learning.

• YouTube
• 22 minutes
• On-Demand
• Conference Talk

Federated Machine Learning with Kubernetes

Explore federated machine learning implementation on Kubernetes, enhancing data privacy and collaboration across distributed datasets without centralized storage.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Simons Institute

Federated and Collaborative Learning - Session 2

Explore cutting-edge research in federated learning, collaborative AI, and privacy-preserving data analysis with expert talks on fast mean estimation and stable covariance techniques.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Alan Turing Institute

A Short Tutorial on Differential Privacy

Explore differential privacy fundamentals, applications in machine learning, and key definitions. Learn about privacy-preserving computations and various mechanisms for protecting sensitive data.

• YouTube
• 1 hour 49 minutes
• On-Demand
• Free Video