Very Large Graph Partitioning by Means of Parallel DBMS. - Constantin S. Pan; Mikhail L. Zymbler (ADBIS, 2013)

Taming Elephants, or How to Embed Parallelism into PostgreSQL. - Constantin S. Pan; Mikhail L. Zymbler (DEXA (1), 2013)

Best-Match Time Series Subsequence Search on the Intel Many Integrated Core Architecture. - Mikhail L. Zymbler (ADBIS, 2015)

Accelerating time series subsequence matching on the Intel Xeon Phi many-core coprocessor. - Ruslan Miniakhmetov; Aleksander Movchan; Mikhail L. Zymbler (MIPRO, 2015)

Time Series Subsequence Similarity Search Under Dynamic Time Warping Distance on the Intel Many-core Accelerators. - Aleksander Movchan; Mikhail L. Zymbler (SISAP, 2015)

Encapsulation of partitioned parallelism into open-source database management systems. - Constantin S. Pan; Mikhail L. Zymbler (Program. Comput. Softw., 2015)

Accelerating Dynamic Itemset Counting on Intel many-core systems. - Mikhail L. Zymbler (MIPRO, 2017)

Integrating DBMS and Parallel Data Mining Algorithms for Modern Many-Core Processors. - Timofey Rechkalov; Mikhail L. Zymbler (DAMDID/RCDL (Selected Papers), 2017)

An Approach to Data Mining inside PostgreSQL Based on Parallel Implementation of UDFs. - Timofey Rechkalov; Mikhail L. Zymbler (DAMDID/RCDL, 2017)

An Efficient Subsequence Similarity Search on Modern Intel Many-core Processors for Data Intensive Applications. - Yana Kraeva; Mikhail L. Zymbler (DAMDID/RCDL, 2018)

Scalable Algorithm for Subsequence Similarity Search in Very Large Time Series Data on Cluster of Phi KNL. - Yana Kraeva; Mikhail L. Zymbler (DAMDID/RCDL (Selected Papers), 2018)

Parallel Algorithm for Frequent Itemset Mining on Intel Many-core Systems. - Mikhail L. Zymbler (J. Comput. Inf. Technol., 2018)

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 L. Zymbler (CoRR, 2018)

An Approach to Fuzzy Clustering of Big Data Inside a Parallel Relational DBMS. - Mikhail L. Zymbler; Yana Kraeva; Alexander Grents; Anastasiya Perkova; Sachin Kumar 001 (DAMDID/RCDL (Selected Papers), 2019)

Big Data Processing and Analytics Inside DBMS. - Mikhail L. Zymbler; Sachin Kumar 001; Yana Kraeva; Alexander Grents; Anastasiya Perkova (DAMDID/RCDL, 2019)

Parallel Algorithm for Time Series Discords Discovery on the Intel Xeon Phi Knights Landing Many-core Processor. - Andrey Polyakov 001; Mikhail L. Zymbler (CoRR, 2019)

Internet of Things is a revolutionary approach for future technology enhancement: a review. - Sachin Kumar 001; Prayag Tiwari; Mikhail L. Zymbler (J. Big Data, 2019)

A machine learning approach to analyze customer satisfaction from airline tweets. - Sachin Kumar 001; Mikhail L. Zymbler (J. Big Data, 2019)

Analyzing MRI scans to detect glioblastoma tumor using hybrid deep belief networks. - Annapareddy V. N. Reddy; Ch. Phani Krishna; Pradeep Kumar Mallick; Sandeep Kumar Satapathy; Prayag Tiwari; Mikhail L. Zymbler; Sachin Kumar 001 (J. Big Data, 2020)

A Novel Algorithmic Forex Trade and Trend Analysis Framework Based on Deep Predictive Coding Network Optimized with Reptile Search Algorithm. - Swaty Dash; Pradip Kumar Sahu; Debahuti Mishra; Pradeep Kumar Mallick; Bharti Sharma; Mikhail L. Zymbler; Sachin Kumar 001 (Axioms, 2022)

Brain Tumor Classification Using Dense Efficient-Net. - Dillip Ranjan Nayak; Neelamadhab Padhy; Pradeep Kumar Mallick; Mikhail L. Zymbler; Sachin Kumar 001 (Axioms, 2022)

Botanical Leaf Disease Detection and Classification Using Convolutional Neural Network: A Hybrid Metaheuristic Enabled Approach. - Madhumini Mohapatra; Ami Kumar Parida; Pradeep Kumar Mallick; Mikhail L. Zymbler; Sachin Kumar 001 (Comput., 2022)

High-performance Time Series Anomaly Discovery on Graphics Processors. - Mikhail L. Zymbler; Yana Kraeva (CoRR, 2023)