Transformers Can Implement Preconditioned Richardson Iteration for In-Context Gaussian Kernel Regression

In this paper, we study in-context kernel ridge regression (KRR) with Gaussian kernels and show, both theoretically and empirically, that a standard softmax-attention transformer can approximate the KRR predictor during its forward pass. Under bounded-data assumptions, we construct a single-head tra