Its use results in faster development, cleaner testbenches, and a modern software-oriented approach to validating FPGA and ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Python libraries handle real business tasks like APIs, data analysis, and machine learning at scaleUsing ready-made libraries reduces coding erro ...

Abstract: In the paper, we propose a novel RaptorQ-based unsourced random access (URA) scheme that integrates RaptorQ codes and sparse regression codes (SPARCs) to design access schemes tailored for ...

Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...

PythoC lets you use Python as a C code generator, but with more features and flexibility than Cython provides. Here’s a first look at the new C code generator for Python. Python and C share more than ...

[~/regression-testing]$ hyperfine --warmup=10 "cp313/python/bin/python3.13 dicttest.py" "cp314/python/bin/python3.14 dicttest.py" Benchmark 1: cp313/python/bin ...

Sometimes, reading Python code just isn’t enough to see what’s really going on. You can stare at lines for hours and still miss how variables change, or why a bug keeps popping up. That’s where a ...

Researchers from Cornell and Google introduce a unified Regression Language Model (RLM) that predicts numeric outcomes directly from code strings—covering GPU kernel latency, program memory usage, and ...