Search Results for author:
Found 8 papers, 1 papers with code
Enhancing Data Provenance and Model Transparency in Federated Learning Systems - A Database Approach
Our findings show that our system can greatly enhance data transparency in various FL environments by storing chained cryptographic hashes and client model snapshots in our proposed design for data decoupled FL.
Smuche: Scalar-Multiplicative Caching in Homomorphic Encryption
A promising strategy to tackle this issue involves optimizing the performance of fully homomorphic encryption (HE).
UCM-Net: A Lightweight and Efficient Solution for Skin Lesion Segmentation using MLP and CNN
Skin cancer poses a significant public health challenge, necessitating efficient diagnostic tools.
Comparative Evaluation of Data Decoupling Techniques for Federated Machine Learning with Database as a Service
To evaluate this approach, the authors develop a framework called Data-Decoupling Federated Learning (DDFL) and compare it with state-of-the-art FL systems that tightly couple data management and computation.
A SVD-based Dynamic Harmonic Phasor Estimator with Improved Suppression of Out-of-Band Interference
The diffusion of nonlinear loads and power electronic devices in power systems deteriorates the signal environment and increases the difficulty of measuring harmonic phasors.
Nonparametric Topological Layers in Neural Networks
Various topological techniques and tools have been applied to neural networks in terms of network complexity, explainability, and performance.
BAASH: Enabling Blockchain-as-a-Service on High-Performance Computing Systems
The state-of-the-art approach to manage blockchains is to process blocks of transactions in a shared-nothing environment.
Distributed, Parallel, and Cluster Computing
The Blockchain Game: Synthesis of Byzantine Systems and Nash Equilibria
This position paper presents a synthesis viewpoint of blockchains from two orthogonal perspectives: fault-tolerant distributed systems and game theory.
