Yaroslav Hayduk

Affiliations:
  • Université de Neuchâtel, Switzerland


According to our database1, Yaroslav Hayduk authored at least 12 papers between 2011 and 2017.

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Bibliography

2017
Exploiting Concurrency and Heterogeneity for Energy-efficient Computing: An Actor-based Approach.
PhD thesis, February, 2017

Towards an Efficient Pauseless Java GC with Selective HTM-Based Access Barriers.
Proceedings of the 14th International Conference on Managed Languages and Runtimes, 2017

2016
Data Mining Meets HCI: Data and Visual Analytics of Frequent Patterns.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Exploiting Concurrency in Domain-Specific Data Structures: A Concurrent Order Book and Workload Generator for Online Trading.
Proceedings of the Networked Systems - 4th International Conference, 2016

Energy minimization at all layers of the data center: The ParaDIME project.
Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition, 2016

Enhanced Energy Efficiency with the Actor Model on Heterogeneous Architectures.
Proceedings of the Distributed Applications and Interoperable Systems, 2016

2015
Dynamic Message Processing and Transactional Memory in the Actor Model.
Proceedings of the Distributed Applications and Interoperable Systems, 2015

2014
ParaDIME: Parallel Distributed Infrastructure for Minimization of Energy.
Proceedings of the 17th Euromicro Conference on Digital System Design, 2014

2013
Speculative Concurrent Processing with Transactional Memory in the Actor Model.
Proceedings of the Principles of Distributed Systems - 17th International Conference, 2013

Mining Frequent Patterns from Uncertain Data with MapReduce for Big Data Analytics.
Proceedings of the Database Systems for Advanced Applications, 2013

2011
A landmark-model based system for mining frequent patterns from uncertain data streams.
Proceedings of the 15th International Database Engineering and Applications Symposium (IDEAS 2011), September 21, 2011

Visually Contrast Two Collections of Frequent Patterns.
Proceedings of the Data Mining Workshops (ICDMW), 2011


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