2.3k citations · 2.4k across the 6 of their papers we have counts for
4 papers · 1 filter
Steering Prototypes with Prompt-tuning for Rehearsal-free Continual Learning
Zhuowei Li, Long Zhao, Zizhao Zhang +4
In the context of continual learning, prototypes-as representative class embeddings-offer advantages in memory conservation and the mitigation of catastrophic forgetting. However,…
DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning
Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi +8
Continual learning aims to enable a single model to learn a sequence of tasks without catastrophic forgetting. Top-performing methods usually require a rehearsal buffer to store pa…
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Kihyuk Sohn, David Berthelot, Chun-Liang Li +6
Semi-supervised learning (SSL) provides an effective means of leveraging unlabeled data to improve a model's performance. In this paper, we demonstrate the power of a simple combin…
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring
David Berthelot, Nicholas Carlini, Ekin D. Cubuk +4
We improve the recently-proposed "MixMatch" semi-supervised learning algorithm by introducing two new techniques: distribution alignment and augmentation anchoring. Distribution al…