research
∙
08/16/2023
Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems?
Recommender systems have become fundamental building blocks of modern on...
share
research
∙
04/13/2023
Physics-informed radial basis network (PIRBN): A local approximation neural network for solving nonlinear PDEs
Our recent intensive study has found that physics-informed neural networ...
research
∙
09/28/2022
Securing Federated Learning against Overwhelming Collusive Attackers
In the era of a data-driven society with the ubiquity of Internet of Thi...
research
∙
09/03/2022
FedAR+: A Federated Learning Approach to Appliance Recognition with Mislabeled Data in Residential Buildings
With the enhancement of people's living standards and rapid growth of co...
research
∙
08/22/2022
A Novel Multi-Task Learning Approach for Context-Sensitive Compound Type Identification in Sanskrit
The phenomenon of compounding is ubiquitous in Sanskrit. It serves for a...
research
∙
08/14/2022
Long-Short History of Gradients is All You Need: Detecting Malicious and Unreliable Clients in Federated Learning
Federated learning offers a framework of training a machine learning mod...
research
∙
06/01/2020
Neural Architecture Search with Reinforce and Masked Attention Autoregressive Density Estimators
Neural Architecture Search has become a focus of the Machine Learning co...
research
∙
05/06/2020
