The assumption running through travel right now is that AI will help solve the industry's labor shortage. Skift tested that ...

Also known as the "Python Huntress," Amy Siewe calls the annual Florida Python Challenge 'a circus and counterproductive.' ...

In this work, we address a question that has attracted intense interest in recent years: whether machine learning-assisted algorithms can genuinely outperform classical approaches in challenging ...

Microsoft Research has released OptiMind, an AI based system that converts natural language descriptions of complex decision problems into mathematical formulations that optimization solvers can ...

Abstract: This study examined how the Ant Colony Optimization (ACO) algorithm could be used to improve urban route planning, using a simulation based on the classic Traveling Salesman Problem (TSP).

Phi-4-reasoning is a 14-billion parameter model specialized in complex reasoning tasks. It is trained using supervised finetuning (SFT) on diverse prompts and reasoning demonstrations from o3-mini.

wordtour.txt is the trained embeddings. The i-th line shows the i-th word in the tour. Note that the embeddings are circular, and thus the first line and the last line are next to each other. The ...

To say that I was raised by 1980s TV is unfair to my wonderful parents, but I certainly spent as much time with the Keatons, the Huxtables, the Seavers, the 4077th, and the Cheers gang as I did around ...

We introduce a method for solving a quadratic unconstrained binary optimization (QUBO) with the two-way one-hot constraints by dividing the QUBO into parts and solving it with an Ising machine. The ...

🚀 Update: If you are interested in this work, you may be interested in our latest paper and up-to-date codebase bringing together several architectures and learning paradigms for learning-driven TSP ...