Why it matters: Linear algebra underpins machine learning, enabling efficient data representation, transformation, and optimization for algorithms like regression, PCA, and neural networks. Python ...

Abstract: Existing loss minimization control (LMC) methods for linear induction machine still suffer from poor parameter robustness and limited effect on system loss suppression. To solve these issues ...

Abstract: The key to optimize the efficiency of permanent magnet synchronous motors (PMSMs) lies in how to obtain accurate and stable loss minimization criteria without solving complex loss equations.

Styblinski-Tang benchmark — a controlled high-dimensional surrogate optimization study using the Styblinski-Tang function across dimensions d ∈ {2, 10, 20, 40, 80}. P→C→Y causal workflow — a ...

Code for Implicit Regularization in Deep Matrix Factorization. The results will be saved at /tmp/ID, where ID is a different number for each run and startsfrom 0.