Using machine learning models to predict if patients have chronic kidney disease based on a few features. The results of the models are also interpreted to make it more understandable to health ...

It can be relatively cheap to gather a lot of bio-signal data. To teach a machine-learning algorithm to find a relationship between bio-signals and health outcomes, however, you need to teach the ...

Then, an online-verifiable initial excitation-based dual-integrator-based learning algorithm is first proposed for establishing data-driven learning algorithm. The optimal data-driven control policy ...

Abstract: Generalized category discovery (GCD ... Recent methods employing contrastive learning neglect potential positives and are decoupled from the clustering objective, leading to biased ...

State Key Laboratory of Urban Water Resource and Environment, School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China ...

A learning algorithm is a mathematical framework or procedure that calculates the best output given a particular set of data. It does this by updating the calculation based on the difference ...

For police recruits in Belfast, the pressure is immense. Facing criminal gangs and divided communities, they don't know who to trust. The odds are, they won't all make it.

The new IBM z17 mainframe features AI capabilities across hardware, software, and systems operations. Deloitte's survey reveals top priorities for AI ethics decision-makers in businesses ...

The proposed method is a combination of signal processing techniques and machine learning algorithms ... different real-world scenarios to evaluate it. FIGURE 1. The block diagram of the proposed ...