School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China ...

According to @transformercircuits, attribution graphs have been developed as a method to address persistent challenges in AI model interpretability. Their recent publication explains how these graphs ...

Recommendation systems have advanced in recent years, but organizations still grapple with heterogeneous, sparse or insufficient data, as well as problems such as repeated patterns (echo chamber ...

How to solve linear programming and quadratic programming with inequality constraint only? For LP, I tried to use OSQP and pass the objective as (None, -c), the equality constraint as (None, None), ...

The term “blockchain” is so widespread that it’s easy to assume it’s synonymous with distributed ledger technology (DLT). But blockchain is only one type of DLT. Another form of DLT, a Directed ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...

Linear inequalities are an essential component of algebra. They involve variables, constants, and inequality signs, depicting a range of solutions rather than one specific solution like an equation ...

The emergence of deep learning has not only brought great changes in the field of image recognition, but also achieved excellent node classification performance in graph neural networks. However, the ...