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Author

Daniel Rodríguez

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Open access 2023

Accelerating Neural Networks with Model Compression Techniques

Experimental results demonstrate that effective compression significantly reduces model size and computational cost with minimal performance loss, highlighting the importance of compression-aware design and concluding as a valuable reference for building efficient and scalable AI systems.

Daniel Rodríguez · 0 citations
2022

Data Science Applications in Financial Risk Assessment

Experimental insights show that models like random forests, gradient boosting, SVMs, and neural networks provide better predictive accuracy and early warning capabilities compared to traditional methods, but challenges related to data quality, interpretability, and ethical concerns remain.

Daniel Rodríguez · 0 citations