A self-explaining rationalization model is generally constructed by a
co...
Rationalization is to employ a generator and a predictor to construct a
...
This paper addresses the temporal sentence grounding (TSG). Although exi...
This paper investigates a new, practical, but challenging problem named
...
Online Class-Incremental (OCI) learning has sparked new approaches to ex...
Federated Learning (FL) is an emerging paradigm that enables distributed...
Multimodal learning (MML) aims to jointly exploit the common priors of
d...
Conventional works generally employ a two-phase model in which a generat...
Traditional one-bit compressed stochastic gradient descent can not be
di...
In the setting of federated optimization, where a global model is aggreg...
In recent years, personalized federated learning (pFL) has attracted
inc...
Federated Learning is a powerful machine learning paradigm to cooperativ...
Distributed asynchronous offline training has received widespread attent...
Gradient descent algorithms are widely used in machine learning. In orde...