Convergence of federated learning over a noisy downlink
… The convergence analysis of the proposed digital downlink … the convergence analysis of the
analog downlink approach, … of a noisy downlink transmission on the convergence behavior. …
analog downlink approach, … of a noisy downlink transmission on the convergence behavior. …
Federated learning over noisy channels: Convergence analysis and design examples
… We present novel convergence analyses of the standard Federated Averaging (FEDAVG) …
transmissions, and simultaneous noisy downlink and uplink analog communications. These …
transmissions, and simultaneous noisy downlink and uplink analog communications. These …
Improved convergence analysis and snr control strategies for federated learning in the presence of noise
A Upadhyay, A Hashemi - IEEE Access, 2023 - ieeexplore.ieee.org
… an improved convergence analysis technique that characterizes the distributed learning
paradigm of federated learning (FL) with imperfect/noisy uplink and downlink communications. …
paradigm of federated learning (FL) with imperfect/noisy uplink and downlink communications. …
Federated learning over noisy channels
… uplink and downlink noisy communications, the same O(1/T) convergence rate of FEDAVG
… the effective noise power of both uplink and downlink to scale at rate O(1/t2) and choose the …
… the effective noise power of both uplink and downlink to scale at rate O(1/t2) and choose the …
Federated learning with downlink device selection
… the convergence of the global model or lack of any participating devices. In this study, we
consider device selection based on downlink … FEEL with noisy bandwidth-limited downlink and …
consider device selection based on downlink … FEEL with noisy bandwidth-limited downlink and …
Design and analysis of uplink and downlink communications for federated learning
… We provide new convergence analysis of the well-known … quantization in uplink and downlink
communications. These … comparing to the noise of SGD, such that the overall “noise level” …
communications. These … comparing to the noise of SGD, such that the overall “noise level” …
Random orthogonalization for federated learning in massive MIMO systems
… interference and noise into consideration, a novel convergence bound of FL … downlink
phases as the theoretical benchmarks. On the machine learning side, we present the convergence …
phases as the theoretical benchmarks. On the machine learning side, we present the convergence …
On the convergence of decentralized federated learning under imperfect information sharing
VP Chellapandi, A Upadhyay… - IEEE Control Systems …, 2023 - ieeexplore.ieee.org
… Motivated by the existing gap between perfect information and noisy decentralized learning,
… Chen, “Design and analysis of uplink and downlink communications for federated learning,” …
… Chen, “Design and analysis of uplink and downlink communications for federated learning,” …
How Robust is Federated Learning to Communication Error? A Comparison Study Between Uplink and Downlink Channels
… downlink, for two reasons. First, for a given BER in the downlink, the local training steps on a
noisy … Proof of Theorem 1 We first prove the convergence bound for FL with uplink bit errors. …
noisy … Proof of Theorem 1 We first prove the convergence bound for FL with uplink bit errors. …
COTAF: Convergent over-the-air federated learning
T Sery, N Shlezinger, K Cohen… - GLOBECOM 2020-2020 …, 2020 - ieeexplore.ieee.org
… effect of the noisy channel, thus facilitating FL convergence. We analyze the convergence of
… , which are commonly more limited as compared to its downlink counterpart [6]. A commonly …
… , which are commonly more limited as compared to its downlink counterpart [6]. A commonly …
相关搜索
- wireless networks federated learning
- over-the air federated learning
- decentralized federated learning
- convergence analysis federated learning
- massive mimo federated learning
- device scheduling federated learning
- privacy leakage federated learning
- robust federated learning
- noisy channels federated learning
- heterogeneous data federated learning
- resource allocation federated learning
- analog federated learning fast convergence algorithm
- uplink and downlink communications federated learning
- quantized federated learning
- fast federated learning
- client selection for federated learning