Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

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 ...
Nature

Inverse Optimization and Linear Programming

Inverse optimisation and linear programming have emerged as crucial instruments in addressing complex decision-making problems where underlying models must be inferred from observed behaviour. At its ...
Wired

AI Models Are Starting to Learn by Asking Themselves Questions

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...
InfoQ

MIT's Recursive Language Models Improve Performance on Long-Context Tasks

Researchers at MIT's CSAIL published a design for Recursive Language Models (RLM), a technique for improving LLM performance on long-context tasks. RLMs use a programming environment to recursively ...
Hosted on MSN

New AI method lets models think harder while avoiding costly bandwidth

DeepSeek’s Engram separates static memory from computation, increasing efficiency in large AI models The method reduces high-speed memory needs by enabling DeepSeek models to use lookups Engram ...
Nature

High-resolution insertion-site analysis by linear amplification–mediated PCR (LAM-PCR)

The design of short LAM-PCR amplicons that do not exceed several hundred base pairs is critical for the efficiency of each analysis. Amplicons should be long enough to be resolved by electropheresis ...
IEEE

Data-Driven Linear Parameter-Varying Model Predictive Control for Unknown Nonlinear Systems

Abstract: This article proposes a data-driven linear parameter variation model predictive control (DDLPVMPC) method for unknown nonlinear (NL) systems. The approach eliminates reliance on prior ...
PC Magazine

The Best Smart Locks for 2026

Forget keys! The top smart locks we've tested are secure, easy to install, and provide several convenient ways to control who can access your home and when. I'm PCMag's managing editor for consumer ...
IEEE

Automatic programming via large language models with population self-evolution for dynamic fuzzy job shop scheduling problem

Abstract: Heuristic dispatching rules (HDRs) are widely used for solving the dynamic fuzzy job shop scheduling problem (DFJSSP). However, their performance is highly sensitive to specific scenarios ...
GitHub

TSalV360: A Method and Dataset for Text-driven Saliency Detection in 360-Degrees Videos

This repository provides code, dataset usage instructions, and trained model from our paper "TSalV360: A Method and Dataset for Text-driven Saliency Detection in 360-Degrees Videos", written by ...
GitHub

AutoJudge – Programming Problem Difficulty Predictor

AutoJudge is a machine learning–based system that predicts the difficulty of programming problems using only their textual descriptions. It outputs both a difficulty class (Easy / Medium / Hard) and a ...