Introducing Cognitive Dissonance Regularization in Deep Learning Models

Explore our innovative research on cognitive dissonance theory integrated with deep learning. We unveil a new regularization framework through theoretical analysis, algorithm design, and experimental validation, ensuring enhanced model robustness and generalization using diverse datasets in text classification and image recognition.

5/8/20241 min read

A workspace featuring a computer monitor displaying lines of code in blue and green on a dark background occupies the center. In the foreground, there is a white coffee mug with a black tree design placed on a wooden desk. Next to the mug, a closed notebook and a book titled 'The Art of Learning' by Josh Waitzkin are laid out. A pen rests on top of the notebook.
A workspace featuring a computer monitor displaying lines of code in blue and green on a dark background occupies the center. In the foreground, there is a white coffee mug with a black tree design placed on a wooden desk. Next to the mug, a closed notebook and a book titled 'The Art of Learning' by Josh Waitzkin are laid out. A pen rests on top of the notebook.

Cognitive Dissonance Framework

Research

Innovative framework for cognitive dissonance regularization.

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