Cellular coverage quality estimation has been a critical task for
self-o...
Accurate routing network status estimation is a key component in Softwar...
We study the problem of training personalized deep learning models in a
...
Federated Learning (FL) is a promising framework for distributed learnin...
In this study, we present a meta-learning model to adapt the predictions...
Self-supervised Learning (SSL) aims at learning representations of objec...
In this paper we present a deep graph reinforcement learning model to pr...
Large scale contextual representation models have significantly advanced...
Real world data is mostly unlabeled or only few instances are labeled.
M...
In this study, we present a dynamic graph representation learning model ...
In recommender systems (RSs), predicting the next item that a user inter...
Predicting the future trajectories of pedestrians is a challenging probl...
Graph representation learning (GRL) is a powerful technique for learning...
Network representation learning (NRL) is a powerful technique for learni...