2 citations · 2 across the 2 of their papers we have counts for
3 papers
Patch-Based Contrastive Learning and Memory Consolidation for Online Unsupervised Continual Learning
Cameron Taylor, Vassilis Vassiliades, Constantine Dovrolis
We focus on a relatively unexplored learning paradigm known as {\em Online Unsupervised Continual Learning} (O-UCL), where an agent receives a non-stationary, unlabeled data stream…
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games
Indranil Sur, Zachary Daniels, Abrar Rahman +16
As Artificial and Robotic Systems are increasingly deployed and relied upon for real-world applications, it is important that they exhibit the ability to continually learn and adap…
Unsupervised Progressive Learning and the STAM Architecture
James Smith, Cameron Taylor, Seth Baer +1
We first pose the Unsupervised Progressive Learning (UPL) problem: an online representation learning problem in which the learner observes a non-stationary and unlabeled data strea…