Metadata
Technology & Computer Science Graduate Create Hard-
Subject
Technology & Computer Science
-
Education level
Graduate
-
Cognitive goals
Create
-
Difficulty estimate
Hard
-
Tags
federated learning, differential privacy, byzantine robustness, IoT, edge computing, scalability
-
Number of questions
5
-
Created on
-
Generation source
-
License
CC0 Public domain
-
Prompt
Assess students' ability to create a novel, scalable federated learning architecture for heterogeneous IoT edge devices that provides provable differential privacy and formal robustness against Byzantine clients. The quiz should test specification of system components (edge, aggregator, hierarchy), algorithms for DP (mechanisms, privacy accounting, composition), Byzantine-robust aggregation strategies and proofs/sketches of robustness under a stated threat model, methods for handling device heterogeneity and resource constraints (partial participation, personalization, compression), scalability techniques (communication reduction, hierarchical/federated aggregation), formal statements and proofs or proof sketches of guarantees, evaluation metrics, and an experimental validation plan.
Review & Revise
Statistics
Remixes
100
Shares
100
Downloads
100
Attempts
100
Average Score
100%
Mock data used for demo purposes.