2 citations · 5 across the 4 of their papers we have counts for
4 papers
High-performance Time Series Anomaly Discovery on Graphics Processors
Mikhail Zymbler, Yana Kraeva
Currently, discovering subsequence anomalies in time series remains one of the most topical research problems. A subsequence anomaly refers to successive points in time that are co…
Parallel Algorithm for Time Series Discords Discovery on the Intel Xeon Phi Knights Landing Many-core Processor
Andrey Polyakov, Mikhail Zymbler
Discord is a refinement of the concept of anomalous subsequence of a time series. The task of discords discovery is applied in a wide range of subject domains related to time serie…
Parallel Algorithm for Frequent Itemset Mining on Intel Many-core Systems
Mikhail Zymbler
Frequent itemset mining leads to the discovery of associations and correlations among items in large transactional databases. Apriori is a classical frequent itemset mining algorit…
The Use of MPI and OpenMP Technologies for Subsequence Similarity Search in Very Large Time Series on Computer Cluster System with Nodes Based on the Intel Xeon Phi Knights Landing Many-core Processor
Yana Kraeva, Mikhail Zymbler
Nowadays, subsequence similarity search is required in a wide range of time series mining applications: climate modeling, financial forecasts, medical research, etc. In most of the…