Search Results for author:
Found 2 papers, 2 papers with code
On the Second-order Convergence Properties of Random Search Methods
We prove that this approach converges to a second-order stationary point at a much faster rate than vanilla methods: namely, the complexity in terms of the number of function evaluations is only linear in the problem dimension.
On Learning the Transformer Kernel
In this work we introduce KERNELIZED TRANSFORMER, a generic, scalable, data driven framework for learning the kernel function in Transformers.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
