Large language models (LLMs) have played a pivotal role in revolutionizi...
Large language models have shown impressive performance in many tasks. O...
Since 2008, after the proposal of a Bitcoin electronic cash system, Bitc...
Weighted low rank approximation is a fundamental problem in numerical li...
Many machine learning algorithms require large numbers of labeled data t...
Tensor decomposition is a fundamental method used in various areas to de...
Many convex optimization problems with important applications in machine...
Large language models (LLMs) have numerous real-life applications across...
Given a matrix M∈ℝ^m× n, the low rank matrix completion
problem asks us ...
Given a matrix A∈ℝ^n× d and a vector b∈ℝ^n, we consider the regression p...