Search Results for author:
Found 10 papers, 5 papers with code
SHFL: Secure Hierarchical Federated Learning Framework for Edge Networks
By aggregating trained models at the edge, SHFL employs two novel methods to address model/data poisoning attacks in the presence of client adversaries: 1) a client selection algorithm running at the edge for choosing IoT devices to participate in training, and 2) a model AGR method designed based on convex optimization theory to reduce the impact of edge models from networks with adversaries in the process of computing the global model (at the cloud level).
CAFe: Cost and Age aware Federated Learning
If enough clients have responded back, the round is deemed successful and the local gradients of all the clients that responded back are used to update the global model.
The Frontier of Data Erasure: Machine Unlearning for Large Language Models
Large Language Models (LLMs) are foundational to AI advancements, facilitating applications like predictive text generation.
DiffPMAE: Diffusion Masked Autoencoders for Point Cloud Reconstruction
By the nature of this reconstruction process, DiffPMAE can be extended to many related downstream tasks including point cloud compression, upsampling and completion.
NetDiffus: Network Traffic Generation by Diffusion Models through Time-Series Imaging
Network data analytics are now at the core of almost every networking solution.
The Wyner Variational Autoencoder for Unsupervised Multi-Layer Wireless Fingerprinting
Our information-theoretic approach can be extended to supervised and semi-supervised settings with straightforward derivations.
3DLatNav: Navigating Generative Latent Spaces for Semantic-Aware 3D Object Manipulation
However, most models do not offer controllability to manipulate the shape semantics of component object parts without extensive semantic attribute labels or other reference point clouds.
CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding
Manual annotation of large-scale point cloud dataset for varying tasks such as 3D object classification, segmentation and detection is often laborious owing to the irregular structure of point clouds.
3D Object Classification
3D Point Cloud Linear Classification
+3
Conservative Plane Releasing for Spatial Privacy Protection in Mixed Reality
Aside from objects being detected, spatial information also reveals the location of the user with high specificity, e. g. in which part of the house the user is.
Characterizing and Detecting Money Laundering Activities on the Bitcoin Network
Bitcoin is by far the most popular crypto-currency solution enabling peer-to-peer payments.
