GitHub

PolyU-IOR/HPR-LP-Python

$$ \begin{array}{ll} \underset{x \in \mathbb{R}^n}{\min} \quad & \langle c, x \rangle \\ \text{s.t.} \quad & L \leq A x \leq U, \\ & l \leq x \leq u . \end{array ...
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 ...
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 ...
scmp.com

DeepSeek kicks off 2026 with paper signalling push to train bigger models for less

Chinese artificial intelligence start-up DeepSeek has ushered in 2026 with a new technical paper, co-authored by founder Liang Wenfeng, that proposes a rethink of the fundamental architecture used to ...
University of Bristol

Introduction to Linear and Logistic Regression Models

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...
Hosted on MSN

'Basically zero, garbage': Renowned mathematician Joel David Hamkins declares AI models useless for solving math. Here's why

Renowned mathematician Joel David Hamkins has expressed strong doubts about large language models' utility in mathematical research, calling their outputs "garbage" and "mathematically incorrect".
IEEE

Integer Ambiguity Baseline Rectifying for GNSS Augmentation Services by Linear Programming Method

Abstract: The advent of the global navigation satellite system has greatly enhanced satellite positioning technology, with precise point positioning (PPP) emerging as a prominent technique. Despite ...
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 ...
www.cs.cmu.edu

Linear and Integer Programming

Write down the Linear Program (LP) relaxation of an IP Plot the graphical representation of an IP and find the optimal solution Understand the relationship between optimal solution of an IP and the ...
XCOM 2 Game Guide

Let’s solve “Cooking method using wet and dry heats” in Cookie Jam

“Cooking method using wet and dry heats” is a confusing question in Cookie Ham if you are not knowledgeable in cooking. Let’s solve “Cooking method using wet and dry heats” in Cookie Jam Source: ...
GitHub

Can Large Language Models Predict Parallel Code Performance?

We took this version of HeCBench and are modifying it to build the CUDA and OMP codes to gather their roofline performance data. So far we have a large portion of the CUDA and OMP codes building ...