Matthias Boehm
TítuloCitado porAño
Systemml: Declarative machine learning on spark
M Boehm, MW Dusenberry, D Eriksson, AV Evfimievski, FM Manshadi, ...
Proceedings of the VLDB Endowment 9 (13), 1425-1436, 2016
792016
Hybrid parallelization strategies for large-scale machine learning in SystemML
M Boehm, S Tatikonda, B Reinwald, P Sen, Y Tian, DR Burdick, ...
Proceedings of the VLDB Endowment 7 (7), 553-564, 2014
632014
Data management in the mirabel smart grid system
M Boehm, L Dannecker, A Doms, E Dovgan, B Filipič, U Fischer, ...
Proceedings of the 2012 Joint EDBT/ICDT Workshops, 95-102, 2012
502012
Efficient in-memory indexing with generalized prefix trees
M Boehm, B Schlegel, PB Volk, U Fischer, D Habich, W Lehner
Datenbanksysteme für Business, Technologie und Web (BTW), 2011
492011
Compressed linear algebra for large-scale machine learning
A Elgohary, M Boehm, PJ Haas, FR Reiss, B Reinwald
Proceedings of the VLDB Endowment 9 (12), 960-971, 2016
482016
Data management in machine learning: Challenges, techniques, and systems
A Kumar, M Boehm, J Yang
Proceedings of the 2017 ACM International Conference on Management of Data …, 2017
422017
Resource elasticity for large-scale machine learning
B Huang, M Boehm, Y Tian, B Reinwald, S Tatikonda, FR Reiss
Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015
382015
SystemML's Optimizer: Plan Generation for Large-Scale Machine Learning Programs.
M Boehm, DR Burdick, AV Evfimievski, B Reinwald, FR Reiss, P Sen, ...
IEEE Data Eng. Bull. 37 (3), 52-62, 2014
282014
SPOOF: Sum-Product Optimization and Operator Fusion for Large-Scale Machine Learning.
T Elgamal, S Luo, M Boehm, AV Evfimievski, S Tatikonda, B Reinwald, ...
CIDR, 2017
242017
Context-aware parameter estimation for forecast models
L Dannecker, R Schulze, M Boehm, W Lehner
US Patent 9,361,273, 2016
212016
DIPBench Toolsuite: A Framework for Benchmarking Integration Systems.
M Böhm, D Habich, W Lehner, U Wloka
ICDE, 1596-1599, 2008
212008
Context-aware parameter estimation for forecast models in the energy domain
L Dannecker, R Schulze, M Böhm, W Lehner, G Hackenbroich
International Conference on Scientific and Statistical Database Management …, 2011
202011
On optimizing machine learning workloads via kernel fusion
A Ashari, S Tatikonda, M Boehm, B Reinwald, K Campbell, J Keenleyside, ...
ACM SIGPLAN Notices 50 (8), 173-182, 2015
182015
Hybrid parallelization strategies for machine learning programs on top of MapReduce
M Boehm, D Burdick, B Reinwald, P Sen, S Tatikonda, Y Tian, ...
US Patent 9,286,044, 2016
172016
Declarative machine learning-a classification of basic properties and types
M Boehm, AV Evfimievski, N Pansare, B Reinwald
arXiv preprint arXiv:1605.05826, 2016
162016
Towards integrated data analytics: Time series forecasting in DBMS
U Fischer, L Dannecker, L Siksnys, F Rosenthal, M Boehm, W Lehner
Datenbank-Spektrum 13 (1), 45-53, 2013
162013
Towards Self-Optimization of Message Transformation Processes.
M Böhm, D Habich, U Wloka, J Bittner, W Lehner
ADBIS Research Communications, 1-10, 2007
152007
Model-Driven Generation and Optimization of Complex Integration Processes.
M Böhm, U Wloka, D Habich, W Lehner
ICEIS (1), 131-136, 2008
142008
Forcasting evolving time series of energy demand and supply
L Dannecker, M Böhm, W Lehner, G Hackenbroich
East European Conference on Advances in Databases and Information Systems …, 2011
132011
Pipelined approach to fused kernels for optimization of machine learning workloads on graphical processing units
A Ashari, M Boehm, KW Campbell, A Evfimievski, JD Keenleyside, ...
US Patent 9,972,063, 2018
122018
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
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