Dictionary Based

Dictionary-based approaches are increasingly used in various fields to represent and process data efficiently, focusing on learning compact representations from data to improve model performance and interpretability. Current research explores applications in image processing (e.g., deblurring, super-resolution), natural language processing (e.g., machine translation, bias mitigation), and time series analysis (e.g., classification), employing algorithms like Temporal Dictionary Ensemble and novel architectures inspired by convolutional kernels. These methods offer advantages in computational efficiency, interpretability, and sometimes accuracy compared to deep learning alternatives, impacting diverse applications from image restoration to improved natural language models.