Over the past few years, various word-level textual attack approaches have been proposed to reveal vulnerability of deep neural networks used in natural language processing. Typically, these involve an important optimization step determine which substitute be for each word original input. However, current research on this is still rather limited, from perspectives both problem-understanding and...

Abstract Parallel implementations of swarm intelligence algorithms such as the ant colony optimization (ACO) have been widely used to shorten execution time when solving complex problems. When aiming for a GPU environment, developing efficient parallel versions using CUDA can be difficult and error-prone task even experienced programmers. To overcome this issue, programming model Algorithmic Sk...

We present a lightweight Coq framework for optimizing tensor kernels written in pure, functional array language. Optimizations rely on user scheduling using series of verified, semantics-preserving rewrites. Unusually compilation targeting imperative code with arrays and nested loops, all rewrites are source-to-source within purely Our language comprises set core constructs expressing high-leve...