Transformers achieve optimal in-context learning for regression

Researchers have developed a method for in-context learning in nonparametric regression using transformers. Their findings indicate that transformers can achieve minimax optimal convergence rates with significantly fewer parameters and pretraining sequences than previously thought. This is accomplished by enabling transformers to approximate local polynomial estimators through a kernel-weighted polynomial basis and gradient descent. AI

影响 Demonstrates a more efficient approach to in-context learning, potentially reducing computational requirements for transformer-based regression tasks.

排序理由 The cluster contains an academic paper detailing a new method for in-context learning with transformers. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv stat.ML 阅读 →

• Tianyi Ma
• Transformers

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