Abstract: We propose reparameterized refocusing convolution (RefConv) as a replacement for regular convolutional layers, which is a plug-and-play module to improve the performance without any ...
Torvalds and the Linux maintainers are taking a pragmatic approach to using AI in the kernel. AI or no AI, it's people, not LLMs, who are responsible for Linux's code. If you try to mess around with ...
KernelOptimizer is an open-source tool that automates CUDA kernel optimization for PyTorch workloads using large language models (LLMs). Inspired by Stanford CRFM’s fast kernel research, it leverages ...
Visual Attention Networks (VANs) leveraging Large Kernel Attention (LKA) have demonstrated remarkable performance in diverse computer vision tasks, often outperforming Vision Transformers (ViTs) in ...
The Linux kernel, foundational for servers, desktops, embedded systems, and cloud infrastructure, has been under heightened scrutiny. Several vulnerabilities have been exploited in real-world attacks, ...
A new Microsoft announcement suggests it has found a way to deliver kernel-level visibility and capabilities to apps running in user mode. Experts conclude a ban on kernel access for cybersecurity ...
Why it matters: The kernel space is the core component of a computer operating system, where critical hardware management and device driver code reside in memory. If a kernel-level driver malfunctions ...
Abstract: Recently, transformers have garnered significant attention due to their exceptional capability to capture long-range dependencies in data. A critical factor contributing to their superior ...
A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results