Search Results for author: Islam Nassar

Found 6 papers, 3 papers with code

All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training

1 code implementation CVPR 2021 Islam Nassar, Samitha Herath, Ehsan Abbasnejad, Wray Buntine, Gholamreza Haffari

We train two classifiers with two different views of the class labels: one classifier uses the one-hot view of the labels and disregards any potential similarity among the classes, while the other uses a distributed view of the labels and groups potentially similar classes together.

Semi-Supervised Image Classification

Generate, Annotate, and Learn: Generative Models Advance Self-Training and Knowledge Distillation

no code implementations29 Sep 2021 Xuanli He, Islam Nassar, Jamie Ryan Kiros, Gholamreza Haffari, Mohammad Norouzi

To obtain strong task-specific generative models, we either fine-tune a large language model (LLM) on inputs from specific tasks, or prompt a LLM with a few input examples to generate more unlabeled examples.

Few-Shot Learning Knowledge Distillation +2

ProtoCon: Pseudo-label Refinement via Online Clustering and Prototypical Consistency for Efficient Semi-supervised Learning

no code implementations CVPR 2023 Islam Nassar, Munawar Hayat, Ehsan Abbasnejad, Hamid Rezatofighi, Gholamreza Haffari

Finally, ProtoCon addresses the poor training signal in the initial phase of training (due to fewer confident predictions) by introducing an auxiliary self-supervised loss.

Online Clustering Pseudo Label

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