5 papers · 1 filter
Achieving Upper Bound Accuracy of Joint Training in Continual Learning
Saleh Momeni, Bing Liu
Continual learning has been an active research area in machine learning, focusing on incrementally learning a sequence of tasks. A key challenge is catastrophic forgetting (CF), an…
Continual Learning Using a Kernel-Based Method Over Foundation Models
Saleh Momeni, Sahisnu Mazumder, Bing Liu
Continual learning (CL) learns a sequence of tasks incrementally. This paper studies the challenging CL setting of class-incremental learning (CIL). CIL has two key challenges: cat…
DESIRE: Dynamic Knowledge Consolidation for Rehearsal-Free Continual Learning
Haiyang Guo, Fei Zhu, Fanhu Zeng +2
Continual learning aims to equip models with the ability to retain previously learned knowledge like a human. Recent work incorporating Parameter-Efficient Fine-Tuning has revitali…
Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach
Chaoxi Niu, Guansong Pang, Ling Chen +1
Class-incremental learning (CIL) aims to continually learn a sequence of tasks, with each task consisting of a set of unique classes. Graph CIL (GCIL) follows the same setting but…
Safety through Permissibility: Shield Construction for Fast and Safe Reinforcement Learning
Alexander Politowicz, Sahisnu Mazumder, Bing Liu
Designing Reinforcement Learning (RL) solutions for real-life problems remains a significant challenge. A major area of concern is safety. "Shielding" is a popular technique to enf…