Market-making algorithms are all about performance. It doesn't really matter where they are deployed: you are essentially always compute constrained. This particular one involved 3 assets trading ...

Background Joint analyses across multiple health datasets can increase statistical power and improve the generalisability of research findings. However, limitations on data sharing often prevent ...

Existing supply chain information security methods all suffer from the difficulty of balancing information sharing efficiency and information privacy protection. Data is prone to leakage, resulting in ...

Abstract: Multiplying matrices can be very challenging although it seems straightforward. Many researchers have studied the multiplication of two 3 by 3 matrices by using Strassen Algorithm in the ...

Timely and accurate detection of foreign objects is crucial for the safe operation of transmission lines in power grid. Currently, object detection models have more and more parameters and their ...

The tiling algorithm for matrix multiplication is a technique that illustrates how to leverage the memory hierarchy to speed up memory-bound operations. At a high level the idea is simple: move blocks ...

Computer scientists at UC Berkeley say that AI models show promise as a way to discover and optimize algorithms. In a preprint paper titled "Barbarians at the Gate: How AI is Upending Systems Research ...

We tried other Python libraries such as python-ecdsa, fast-ecdsa and other less famous ones, but we didn't find anything that suited our needs. The first one was pure Python, but it was too slow. The ...

For this introduction I am going to define key terms so we can do into more depth about the applications and uses of data structures and algorithms. These will be the key terms defined in this section ...

Optical neural networks (ONNs) promise computing efficiency beyond microelectronics for modern artificial intelligence (AI). Current ONNs using analog matrix-vector multiplication (MVM) ...