Due to advancements in data collection, storage, and processing techniques, machine
learning has become a thriving and dominant paradigm. However, one of its main …

Despite the advancement of machine learning techniques in recent years, state-of-the-art
systems lack robustness to “real world” events, where the input distributions and tasks …

Continual learning algorithms which keep the parameters of new tasks close to that of
previous tasks, are popular in preventing catastrophic forgetting in sequential task learning …

As more and more AI agents are used in practice, it is time to think about how to make these
agents fully autonomous so that they can (1) learn by themselves continually in a self …

Lifelong Learning (LL) refers to the ability to continually learn and solve new problems with
incremental available information over time while retaining previous knowledge. Much …

3D object classification has been widely applied in both academic and industrial scenarios.
However, most state-of-the-art algorithms rely on a fixed object classification task set, which …

The visual perception systems aim to autonomously collect consecutive visual data and
perceive the relevant information online like human beings. In comparison with the classical …

Learning is a process wherein a learning agent enhances its performance through exposure
of experience or data. Throughout this journey, the agent may encounter diverse learning …

Effective lifelong learning across diverse tasks requires the transfer of diverse knowledge,
yet transferring irrelevant knowledge may lead to interference and catastrophic forgetting. In …

This work studies the intersection of continual and federated learning, in which independent
agents face unique tasks in their environments and incrementally develop and share …