Search Results for author:
Found 5 papers, 1 papers with code
Overcoming Growth-Induced Forgetting in Task-Agnostic Continual Learning
In continual learning (CL), model growth enhances adaptability over new data, improving knowledge retention for more tasks.
FedDistill: Global Model Distillation for Local Model De-Biasing in Non-IID Federated Learning
This paper introduces FedDistill, a framework enhancing the knowledge transfer from the global model to local models, focusing on the issue of imbalanced class distribution.
A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist
Notably, FinAgent is the first advanced multimodal foundation agent designed for financial trading tasks.
MGAS: Multi-Granularity Architecture Search for Trade-Off Between Model Effectiveness and Efficiency
However, existing DAS methods fail to trade off between model performance and model size.
AdaptCL: Adaptive Continual Learning for Tackling Heterogeneity in Sequential Datasets
Managing heterogeneous datasets that vary in complexity, size, and similarity in continual learning presents a significant challenge.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
