Federated Design of Compact and Private DNNs

Federated Design of Compact and Private DNNs

Channel:
United States Google TechTalks
Subscribers:
348,000
Published on ● Video Link: https://www.youtube.com/watch?v=ps5PcNVc3Vw


Duration: 17:52
203 views
3

A Google TechTalk, 2020/7/29, presented by Farinaz Koushanfar, UCSD
ABSTRACT:



Other Videos By Google TechTalks


2021-09-29A Geometric View on Private Gradient-Based Optimization
2021-09-29BB84: Quantum Protected Cryptography
2021-09-29Fast and Memory Efficient Differentially Private-SGD via JL Projections
2021-09-29Leveraging Public Data for Practical Synthetic Data Generation
2021-07-13Efficient Exploration in Bayesian Optimization – Optimism and Beyond by Andreas Krause
2021-07-13Learning to Explore in Molecule Space by Yoshua Bengio
2021-07-13Resource Allocation in Multi-armed Bandits by Kirthevasan Kandasamy
2021-07-13Grey-box Bayesian Optimization by Peter Frazier
2021-06-10Is There a Mathematical Model of the Mind? (Panel Discussion)
2021-06-04Dataset Poisoning on the Industrial Scale
2021-06-04Federated Design of Compact and Private DNNs
2021-06-04Workshop on Federated Learning and Analytics: Pre-recorded Talks Day 2 Track 2 Q&A Privacy/Security
2021-06-04Privacy-Preserving Analytics on the Edge
2021-06-04Google Workshop on Federated Learning and Analytics: Talks from Google
2021-06-04Workshop on Federated Learning & Analytics: Pre-recorded Talks Day 2 Track 1 Q&A Optimization/System
2021-06-04Learning discrete distributions: User vs item-level privacy
2021-06-04TensorFlow Federated Tutorial Session
2021-06-04Attack of the Tails: Yes, you Really can Backdoor Federated Learning
2021-06-04FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning
2021-06-04Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning
2021-06-04Domain Compression: A primitive for distributed inference under communication & privacy constraints