Mikhail L. Zymbler

24 papers B 1C 2Journal 12Unranked 9
YearRankTypeTitle / Venue / Authors
2023 J jnl
High-performance Time Series Anomaly Discovery on Graphics Processors.
CoRR
Mikhail L. Zymbler, Yana Kraeva
2022 J jnl
A Novel Algorithmic Forex Trade and Trend Analysis Framework Based on Deep Predictive Coding Network Optimized with Reptile Search Algorithm.
Axioms
Swaty Dash, Pradip Kumar Sahu, Debahuti Mishra, Pradeep Kumar Mallick, Bharti Sharma, Mikhail L. Zymbler, Sachin Kumar
2022 J jnl
Botanical Leaf Disease Detection and Classification Using Convolutional Neural Network: A Hybrid Metaheuristic Enabled Approach.
Comput.
Madhumini Mohapatra, Ami Kumar Parida, Pradeep Kumar Mallick, Mikhail L. Zymbler, Sachin Kumar
2022 J jnl
Brain Tumor Classification Using Dense Efficient-Net.
Axioms
Dillip Ranjan Nayak, Neelamadhab Padhy, Pradeep Kumar Mallick, Mikhail L. Zymbler, Sachin Kumar
2020 J jnl
Analyzing MRI scans to detect glioblastoma tumor using hybrid deep belief networks.
J. Big Data
Annapareddy V. N. Reddy, Ch. Phani Krishna, Pradeep Kumar Mallick, Sandeep Kumar Satapathy, Prayag Tiwari, Mikhail L. Zymbler, Sachin Kumar
2019 J jnl
A machine learning approach to analyze customer satisfaction from airline tweets.
J. Big Data
Sachin Kumar, Mikhail L. Zymbler
2019 — conf
An Approach to Fuzzy Clustering of Big Data Inside a Parallel Relational DBMS.
DAMDID/RCDL (Selected Papers)
Mikhail L. Zymbler, Yana Kraeva, Alexander Grents, Anastasiya Perkova, Sachin Kumar
2019 — conf
Big Data Processing and Analytics Inside DBMS.
DAMDID/RCDL
Mikhail L. Zymbler, Sachin Kumar, Yana Kraeva, Alexander Grents, Anastasiya Perkova
2019 J jnl
Internet of Things is a revolutionary approach for future technology enhancement: a review.
J. Big Data
Sachin Kumar, Prayag Tiwari, Mikhail L. Zymbler
2019 J jnl
Parallel Algorithm for Time Series Discords Discovery on the Intel Xeon Phi Knights Landing Many-core Processor.
CoRR
Andrey Polyakov, Mikhail L. Zymbler
2018 — conf
An Efficient Subsequence Similarity Search on Modern Intel Many-core Processors for Data Intensive Applications.
DAMDID/RCDL
Yana Kraeva, Mikhail L. Zymbler
2018 J jnl
Parallel Algorithm for Frequent Itemset Mining on Intel Many-core Systems.
J. Comput. Inf. Technol.
Mikhail L. Zymbler
2018 J jnl
Parallel Algorithm for Frequent Itemset Mining on Intel Many-core Systems.
CoRR
Mikhail L. Zymbler
2018 — conf
Scalable Algorithm for Subsequence Similarity Search in Very Large Time Series Data on Cluster of Phi KNL.
DAMDID/RCDL (Selected Papers)
Yana Kraeva, Mikhail L. Zymbler
2018 J jnl
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.
CoRR
Yana Kraeva, Mikhail L. Zymbler
2017 — conf
Accelerating Dynamic Itemset Counting on Intel many-core systems.
MIPRO
Mikhail L. Zymbler
2017 — conf
An Approach to Data Mining inside PostgreSQL Based on Parallel Implementation of UDFs.
DAMDID/RCDL
Timofey Rechkalov, Mikhail L. Zymbler
2017 — conf
Integrating DBMS and Parallel Data Mining Algorithms for Modern Many-Core Processors.
DAMDID/RCDL (Selected Papers)
Timofey Rechkalov, Mikhail L. Zymbler
2015 — conf
Accelerating time series subsequence matching on the Intel Xeon Phi many-core coprocessor.
MIPRO
Ruslan Miniakhmetov, Aleksander Movchan, Mikhail L. Zymbler
2015 C conf
Best-Match Time Series Subsequence Search on the Intel Many Integrated Core Architecture.
ADBIS
Mikhail L. Zymbler
2015 J jnl
Encapsulation of partitioned parallelism into open-source database management systems.
Program. Comput. Softw.
Constantin S. Pan, Mikhail L. Zymbler
2015 B conf
Time Series Subsequence Similarity Search Under Dynamic Time Warping Distance on the Intel Many-core Accelerators.
SISAP
Aleksander Movchan, Mikhail L. Zymbler
2013 — conf
Taming Elephants, or How to Embed Parallelism into PostgreSQL.
DEXA (1)
Constantin S. Pan, Mikhail L. Zymbler
2013 C conf
Very Large Graph Partitioning by Means of Parallel DBMS.
ADBIS
Constantin S. Pan, Mikhail L. Zymbler