Search Results for author:
Found 4 papers, 1 papers with code
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity
Motivated by high resource costs of centralized machine learning schemes as well as data privacy concerns, federated learning (FL) emerged as an efficient alternative that relies on aggregating locally trained models rather than collecting clients' potentially private data.
Communication-Efficient Variance-Reduced Decentralized Stochastic Optimization over Time-Varying Directed Graphs
To our knowledge, this is the first decentralized optimization framework for time-varying directed networks that achieves such a convergence rate and applies to settings requiring sparsified communication.
Decentralized Optimization On Time-Varying Directed Graphs Under Communication Constraints
We propose a communication-efficient algorithm for decentralized convex optimization that rely on sparsification of local updates exchanged between neighboring agents in the network.
Fitness Done Right: a Real-time Intelligent Personal Trainer for Exercise Correction
Finally, key values for key features of the two poses are computed correspondingly in the pose error detection part, which helps give correction advice.
