Revisiting Generalization: Unpacking Double Descent in Over-Parameterized Models
This research delves into the complexities of generalization in deep learning, distinguishing between strict and weak generalization and exploring new thresholds that redefine our understanding of model performance in over-parameterized regimes.
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Prompt
Create a vertically-oriented academic research poster (80cm x 150cm) with a clean, professional design. Include sections for: Title, Authors and affiliations, Abstract, Introduction/Background, Methodology, Results, Discussion/Conclusion, References, and Acknowledgements/Funding. Use a clean academic color scheme (blues, whites, grays), clear section headings, and appropriate spacing. The poster should be about generalization in over-parameterized models, specifically discussing "Strict vs. Weak Generalization in Over-Parameterized Models". Include placeholder areas for graphs or figures in the Results section. Make sure all text areas are clearly delineated with appropriate font hierarchy (large titles, medium headings, smaller body text).
