Sentence examples for techniques of machine from inspiring English sources

Those same techniques of machine learning and AI can be brought to bear in the massive scientific puzzle of cancer.

People Finder [17] takes a different direction, applying techniques of machine learning to automatically adjust each user's policy, based on their satisfaction with the location information disclosure.

After this, we employed three combinations of state-vector definitions (to model a linear or nonlinear echo path) and observation equations (mathematical relation between state vector and observation) to apply fundamental techniques of machine learning research.

"Machine learning is evolving very rapidly, and there's been a lot of recent work on applying techniques of machine learning to areas like music".

Although the general problem of finding the shortest proofs by means of cut-introduction is undecidable [5], there are a few preliminary algorithms that introduce simple cuts [10,15,24], and it has been shown that some techniques of machine learning, such as decision tree learning, can be seen as cut-introduction techniques from a proof-theoretical point of view [23].

In this paper we show Renaissance of machines as the developments occurred since early modern approaches in 14th century; through activity in 15th century that gave dignity to technique of machines and its professionals; in 16th century when machine experts were well recognized; in 17th century when academic formation on machine knowledge was started.

This paper reports on experiments where techniques of supervised machine learning are applied to the problem of planning.

In Reference [117], for this study, the techniques of virtual machine migration are understood, and the affected reduplications on migration are evaluated.

Finally, they presented future research challenges pertinent to the modeling methods and mitigation techniques of virtual machine performance overhead in the IaaS cloud [17].

We compare the LP method to the standard machine learning techniques of support vector machines (SVM) and the Lasso.

With the aid of modern neuroimaging techniques, the capability of machine learning algorithms to identify distributed patterns of voxels in response to stimuli allows for decoding brain activities using data-driven models.