Schedule

Date	Topic	References
Week 1
Aug 26	Logistics & Introduction (I)	Advances and Open Problems in Federated Learning Federated Learning: Challenges, Methods, and Future Directions
Aug 28	Introduction (II)	Federated Learning Tutorial (NeurIPS 2020) Google Blog Tips for Writing Technical Papers
Week 2
Sep 2	Labor Day (no class)
Sep 4	Communication-Efficient Learning of Deep Networks from Decentralized Data Towards Federated Learning at Scale: System Design
Week 3
Sep 9	Federated Optimization in Heterogeneous Networks SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
Sep 11	Adaptive Federated Optimization Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
Week 4
Sep 16	Federated Learning with Non-IID Data Local SGD Converges Fast and Communicates Little
Sep 18	Federated Learning with Matched Averaging Model-Contrastive Federated Learning
Week 5
Sep 23	Federated Learning: Strategies for Improving Communication Efficiency Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization
Sep 25	Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization
Week 6
Sep 30	The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Communication Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD
Oct 2	Variance Reduced Local SGD with Lower Communication Complexity FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning
Week 7
Oct 7	LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets FedExP: Speeding Up Federated Averaging via Extrapolation
Oct 9	One-Shot Federated Learning Toward resource-efficient federated learning in mobile edge computing
Week 8
Oct 14	Project Proposal Presentations
Oct 16	Project Proposal Presentations
Week 9
Oct 21	Model Pruning Enables Efficient Federated Learning on Edge Devices Energy Efficient Federated Learning Over Wireless Communication Networks
Oct 23	HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients FedFQ: Federated Learning with Fine-Grained Quantization
Week 10
Oct 28	FedMask: Joint Computation and Communication-Efficient Personalized Federated Learning via Heterogeneous Masking Asynchronous Online Federated Learning for Edge Devices with Non-IID Data
Oct 30	Enhancing Convergence in Federated Learning: A Contribution-Aware Asynchronous Approach Oort: Efficient Federated Learning via Guided Participant Selection
Week 11
Nov 4	Ditto: Fair and Robust Federated Learning Through Personalization Practical Secure Aggregation for Privacy-Preserving Machine Learning
Nov 6	How To Backdoor Federated Learning Can You Really Backdoor Federated Learning?
Week 12
Nov 11	Attack of the Tails: Yes, You Really Can Backdoor Federated Learning Evaluating Gradient Inversion Attacks and Defenses in Federated Learning
Nov 13	Federated Learning with Differential Privacy: Algorithms and Performance Analysis PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments
Week 13
Nov 18	Practical Secure Aggregation for Federated Learning on User-Held Data BatchCrypt: Efficient Homomorphic Encryption for Cross-Silo Federated Learning
Nov 20	Towards Building the Federated GPT: Federated Instruction Tuning Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models
Week 14
Nov 25	The Future of Large Language Model Pre-training is Federated OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning
Nov 27	Thanksgiving (no class)
Week 15
Dec 2	Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly Vulnerabilities of Foundation Model Integrated Federated Learning Under Adversarial Threats
Dec 4	Final Project Presentations
Week 16
Dec 9 (Last Day of Classes)	Final Project Presentations