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Boehm, Matthias
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1

Special issue on "Machine learning and databases":

Boehm, Matthias ; Tatbul, Nesime
The VLDB Journal.  , 2024
Link: https://doi.org/10.1007/..
 
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2

POLAR: Adaptive and Non-invasive Join Order Selection via P..:

Justen, David ; Ritter, Daniel ; Fraser, Campbell...
Proceedings of the VLDB Endowment.  17 (2024)  6 - p. 1350-1363 , 2024
Link: https://doi.org/10.14778..
 
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3

UPLIFT: parallelization strategies for feature transformati..:

Phani, Arnab ; Erlbacher, Lukas ; Boehm, Matthias
Proceedings of the VLDB Endowment.  15 (2022)  11 - p. 2929-2938 , 2022
Link: https://doi.org/10.14778..
 
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4

Technical Perspective: Declarative Recursive Computation on..:

Boehm, Matthias
ACM SIGMOD Record.  49 (2020)  1 - p. 42-42 , 2020
Link: https://doi.org/10.1145/..
 
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5

Technical Perspective : Declarative Recursive Computatio..:

Boehm, Matthias
ACM SIGMOD Record.  49 (2020)  1 - p. 42 ff. , 2020
Link: https://dl.acm.org/doi/1..
 
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6

Compressed linear algebra for declarative large-scale machi..:

Elgohary, Ahmed ; Boehm, Matthias ; Haas, Peter J...
Communications of the ACM.  62 (2019)  5 - p. 83-91 , 2019
Link: https://doi.org/10.1145/..
 
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7

Compressed linear algebra for declarative large-scale machi..:

Elgohary, Ahmed ; Boehm, Matthias ; Haas, Peter J...
Communications of the ACM.  62 (2019)  5 - p. 83-91 , 2019
Link: https://dl.acm.org/doi/1..
 
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8

On optimizing operator fusion plans for large-scale machine..:

Boehm, Matthias ; Reinwald, Berthold ; Hutchison, Dylan...
Proceedings of the VLDB Endowment.  11 (2018)  12 - p. 1755-1768 , 2018
Link: https://dl.acm.org/doi/1..
 
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9

On optimizing operator fusion plans for large-scale machine..:

Boehm, Matthias ; Reinwald, Berthold ; Hutchison, Dylan...
Proceedings of the VLDB Endowment.  11 (2018)  12 - p. 1755-1768 , 2018
Link: https://doi.org/10.14778..
 
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10

Scaling Machine Learning via Compressed Linear Algebra:

Elgohary, Ahmed ; Boehm, Matthias ; Haas, Peter J...
ACM SIGMOD Record.  46 (2017)  1 - p. 42-49 , 2017
Link: https://doi.org/10.1145/..
 
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11

Compressed linear algebra for large-scale machine learning:

Elgohary, Ahmed ; Boehm, Matthias ; Haas, Peter J...
The VLDB Journal.  27 (2017)  5 - p. 719-744 , 2017
Link: https://doi.org/10.1007/..
 
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12

Scaling Machine Learning via Compressed Linear Algebra:

Elgohary, Ahmed ; Boehm, Matthias ; Haas, Peter J...
ACM SIGMOD Record.  46 (2017)  1 - p. 42-49 , 2017
Link: https://dl.acm.org/doi/1..
 
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13

Compressed linear algebra for large-scale machine learning:

Elgohary, Ahmed ; Boehm, Matthias ; Haas, Peter J...
Proceedings of the VLDB Endowment.  9 (2016)  12 - p. 960-971 , 2016
Link: https://dl.acm.org/doi/1..
 
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14

SystemML : declarative machine learning on spark:

Boehm, Matthias ; Dusenberry, Michael W. ; Eriksson, Deron...
Proceedings of the VLDB Endowment.  9 (2016)  13 - p. 1425-1436 , 2016
Link: https://dl.acm.org/doi/1..
 
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15

SystemML: declarative machine learning on spark:

Boehm, Matthias ; Dusenberry, Michael W. ; Eriksson, Deron...
Proceedings of the VLDB Endowment.  9 (2016)  13 - p. 1425-1436 , 2016
Link: https://doi.org/10.14778..
 
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