Search Results for author:
Found 5 papers, 0 papers with code
ChatPattern: Layout Pattern Customization via Natural Language
Existing works focus on fixed-size layout pattern generation, while the more practical free-size pattern generation receives limited attention.
On the Evaluation of Generative Models in Distributed Learning Tasks
First, we focus on the Fr\'echet inception distance (FID) and consider the following FID-based aggregate scores over the clients: 1) FID-avg as the mean of clients' individual FID scores, 2) FID-all as the FID distance of the trained model to the collective dataset containing all clients' data.
FedLPA: Personalized One-shot Federated Learning with Layer-Wise Posterior Aggregation
Efficiently aggregating trained neural networks from local clients into a global model on a server is a widely researched topic in federated learning.
Federated Learning with Classifier Shift for Class Imbalance
Federated learning aims to learn a global model collaboratively while the training data belongs to different clients and is not allowed to be exchanged.
DiffPattern: Layout Pattern Generation via Discrete Diffusion
Deep generative models dominate the existing literature in layout pattern generation.
