"In machine learning, local minima—not global minima—are what practical algorithms find and use successfully. This sparked ...

Opinion: Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

shenzhen, May 20, 2025 (GLOBE NEWSWIRE) -- Shenzhen, May. 20, 2025/––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), announced that quantum algorithms will be deeply integrated ...

Mathematical optimization and machine learning are two tools that, at first glance, may seem to have a lot in common. Newsletters Games Share a News Tip Featured ...

ML algorithms can help identify areas where improvements should be made for greater efficiency and cost savings. Businesses that optimize their supply chains can select their best options and in turn ...

Leverages several algorithmic approaches: AutoML relies on Bayesian, evolutionary, regression, meta-learning, transfer learning, combinatorial optimization, and reinforcement learning algorithms. Hubs ...

The Data Science Lab. How to Do Machine Learning Evolutionary Optimization Using C#. Resident data scientist Dr. James McCaffrey of Microsoft Research turns his attention to evolutionary optimization, ...

MicroAlgo Inc. Develops Classifier Auto-Optimization Technology Based on Variational Quantum Algorithms, Accelerating the Advancement of Quantum Machine Learning PR Newswire Fri, May 2, 2025, 11: ...

Figure 1 | Humans versus machine learning for reaction optimization. Shields et al. 4 have developed a machine-learning algorithm that optimizes the outcome of chemical reactions, and tested it in ...