35 citations · 68 across the 22 of their papers we have counts for
6 papers · 1 filter
Topology-Independent Robustness of the Weighted Mean under Label Poisoning Attacks in Heterogeneous Decentralized Learning
Jie Peng, Weiyu Li, Stefan Vlaski +1
Robustness to malicious attacks is crucial for practical decentralized signal processing and machine learning systems. A typical example of such attacks is label poisoning, meaning…
Binary and Ternary Quantization Can Enhance Feature Discrimination
Weizhi Lu, Mingrui Chen, Weiyu Li
Quantization is widely applied in machine learning to reduce computational and storage costs for both data and models. Considering that classification tasks are fundamental to the…
Mean Aggregator is More Robust than Robust Aggregators under Label Poisoning Attacks on Distributed Heterogeneous Data
Jie Peng, Weiyu Li, Stefan Vlaski +1
Robustness to malicious attacks is of paramount importance for distributed learning. Existing works usually consider the classical Byzantine attacks model, which assumes that some…
Byzantine-Robust Decentralized Stochastic Optimization with Stochastic Gradient Noise-Independent Learning Error
Jie Peng, Weiyu Li, Qing Ling
This paper studies Byzantine-robust stochastic optimization over a decentralized network, where every agent periodically communicates with its neighbors to exchange local models, a…
Cascaded Compressed Sensing Networks: A Reversible Architecture for Layerwise Learning
Weizhi Lu, Mingrui Chen, Kai Guo +1
Recently, the method that learns networks layer by layer has attracted increasing interest for its ease of analysis. For the method, the main challenge lies in deriving an optimiza…
Sparse Matrix-based Random Projection for Classification
Weizhi Lu, Weiyu Li, Kidiyo Kpalma +1
As a typical dimensionality reduction technique, random projection can be simply implemented with linear projection, while maintaining the pairwise distances of high-dimensional da…