Sentence examples for statistical learning algorithms from inspiring English sources
Statistical "learning algorithms" — methods of constructing models from streams of data — were the wheel on which the back of the A.I. culture was broken.
SVMs is firmly based on the theory of statistical learning algorithms, uses classification technique by introducing radial basis function (RBF) kernel function.
Previously worked as an Algorithm Engineer Manager at Meituan, leading an algorithm engineers' team to develop cutting-edge Machine Learning or statistical learning algorithms to estimate real-time ETA and do counterfactual analysis.
In addition, D-Trigger is able to accommodate a broad set of statistical learning algorithms for the detection of various unusual events, including botnet attacks, volume anomalies in an ISP network, electric power grid anomalies, etc.
A common goal of computational neuroscience and of artificial intelligence research based on statistical learning algorithms is the discovery and understanding of computational principles that could explain what we consider adaptive intelligence, in animals as well as in machines.
Statistical learning algorithms can then be used to detect relationships between mental encodings and BOLD responses, typically through pattern classification.
The proposed model is based on a multi-network architecture which incorporates multiple Matching Units trained by a statistical learning algorithm (LWPR).
A support vector machine (SVM) based on the statistical learning algorithm is used for estimation of the exposed temperature of fire-damaged concrete structures.
However, as any statistical learning algorithm, SVM's accuracy drops if some of the training points are contaminated by an unknown source of noise.
We use Self-Organizing Maps (SOM), a topologically constrained unsupervised statistical learning algorithm, to characterize the geophysical and mineralogical signatures of regolith and bedrock.
Our method endows the Structural Expectation-Maximization (SEM) statistical learning algorithm with the ability to recognize long-range correlations in a temporal data stream, and create hidden state variables in order to account for such correlations.
