Solutions to the Traveling Salesperson Problem (TSP) have practical applications to processes in transportation, logistics, and automation, yet must be computed with minimal delay to satisfy the real-time nature of the underlying tasks. However, solving large TSP instances quickly without sacrificing solution quality remains challenging for current approximate algorithms. To close this gap, we present a hybrid data-driven approach for solving the TSP based on Graph Neural Networks (GNNs) and Guided Local Search (GLS). Our model predicts the regret of including each edge of the problem graph in the solution; GLS uses these predictions in conjunction with the original problem graph to find solutions. Our experiments demonstrate that this approach converges to optimal solutions at a faster rate than state-of-the-art learning-based approaches and non-learning GLS algorithms for the TSP, notably finding optimal solutions to 96% of the 50-node problem set, 7% more than the next best benchmark, and to 20% of the 100-node problem set, 4.5x more than the next best benchmark. When generalizing from 20-node problems to the 100-node problem set, our approach finds solutions with an average optimality gap of 2.5%, a 10x improvement over the next best learning-based benchmark.

"Good course for anyone who wants to make some sense of all the proper terminology and basic methodology of AI. Idan's explanations are very clear and to the point, no fluff and no distractions!" "The course was actually amazing, giving me much more insight into AI. "It was a great experience." "Indeed a good beginner's course which I actually wanted".

This post contains a list of the AI-related seminars that are scheduled to take place between 11 October and 30 November 2021. All events detailed here are free and open for anyone to attend virtually. Python for explainable, reproducible and applicable machine learning Speaker: Nuutti Sten (City of Helsinki) Organised by: Finnish Centre for AI Sign up to the mailing list for information on how to join. Modern Neural Probabilistic Forecasting Speaker: Kashif Rasul (Morgan Stanley) Organised by: Carnegie Mellon University The Zoom link is here. NVAITC Webinar Series on AI Applications in Computational Sciences: AI meets Nuclear Fusion Speaker: Diogo R. Ferreira (University of Lisbon) Organised by: Finnish Centre for AI Zoom link here.

So you know the theory of Machine Learning and know how to create your first algorithms. There are tons of courses out there about the underlying theory of Machine Learning which don't go any deeper – into the applications. This course is not one of them. Are you ready to apply all of the theory and knowledge to real life Machine Learning challenges? We gathered best industry professionals with tons of completed projects behind.

Artificial intelligence is growing exponentially. There is no doubt about that. Self-driving cars are clocking up millions of miles, IBM Watson is diagnosing patients better than armies of doctors and Google Deepmind's AlphaGo beat the World champion at Go - a game where intuition plays a key role. But the further AI advances, the more complex become the problems it needs to solve. And only Deep Learning can solve such complex problems and that's why it's at the heart of Artificial intelligence.

We are very excited to organize Global Artificial Intelligence(AI) Virtual Conference is held on Oct 11th to Oct 15th 2021. As we get closer to the conference, we want to invite you to participate in Global Big Data Conference Webinar - Online Warm-Up on Oct 7th (1.00PM - 2.15PM) PST. We will features with speakers from our upcoming Global AI Virtual Conference each of which will present a 15 minute sessions. Welcome to webinar hosted by Global Big Data Conference! In the last decade many different types of neural networks have been developed.

The main goal of this experiment, according to the researchers, is to train a machine learning algorithm that could be used to drive the legs of robots in …

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Self-driving cars have rapidly become one of the most transformative technologies to emerge. Fuelled by Deep Learning algorithms, they are continuously driving our society forward and creating new opportunities in the mobility sector. Deep Learning jobs command some of the highest salaries in the development world. This is the first, and only course which makes practical use of Deep Learning, and applies it to building a self-driving car, one of the most disruptive technologies in the world today. With over 28000 students, Rayan is a highly rated and experienced instructor who has followed a "learn by doing" style to create this amazing course.