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MAMUT: Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-User Video Transcoding.

L. Costero, A. Iranfar, M. Zapater, F. Igual, K. Olcoz, and D. Atienza. DATE, page 558-563. IEEE, (2019)

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Marina Maier

Monitoring, Mobilität und Bioverfügbarkeit von Palladiumemissionen aus KraftfahrzeugenM. Maier. TU München, (2010)

Marina Mikhaylova

Molecular dynamics of the neuronal Ca_1hn2_1hn+-binding proteins caldendrin and calneuronM. Mikhaylova. Uni Magdeburg, (2009)

Marina Tsoi

Marina Kopp

Marina Petrova

Other publications of authors with the same name

Self-organizing Maps versus Growing Neural Gas in Detecting Anomalies in Data Centres.M. Zapater, D. Fraga, P. Malagón, Z. Bankovic, and J. Moya. Log. J. IGPL, 23 (3): 495-505 (2015)Enabling Optimal Power Generation of Flow Cell Arrays in 3D MPSoCs with On-Chip Switched Capacitor Converters.H. Najibi, J. Hunter, A. Levisse, M. Zapater, M. Vasic, and D. Atienza. ISVLSI, page 18-23. IEEE, (2020)Comparative study of meta-heuristic 3D floorplanning algorithms.A. Cuesta-Infante, J. Colmenar, Z. Bankovic, J. Risco-Martín, M. Zapater, J. Hidalgo, J. Ayala, and J. Moya. Neurocomputing, (2015)RFID Performance in Localization Systems.I. Álvarez, P. Malagón, M. Zapater, J. de Goyeneche, and J. Moya. IWAAL, volume 6693 of Lecture Notes in Computer Science, page 73-78. Springer, (2011)Dynamic workload and cooling management in high-efficiency data centers.M. Zapater, A. Turk, J. Moya, J. Ayala, and A. Coskun. IGSC, page 1-8. IEEE Computer Society, (2015)MAMUT: Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-User Video Transcoding.L. Costero, A. Iranfar, M. Zapater, F. Igual, K. Olcoz, and D. Atienza. DATE, page 558-563. IEEE, (2019)Design Optimization of 3D Multi-Processor System-on-Chip with Integrated Flow Cell Arrays.A. Andreev, F. Kaplan, M. Zapater, A. Coskun, and D. Atienza. ISLPED, page 42:1-42:6. ACM, (2018)Challenges in Deeply Heterogeneous High Performance Systems.G. Agosta, W. Fornaciari, D. Atienza, R. Canal, A. Cilardo, J. Flich, C. Hernández, M. Kulczewski, G. Massari, R. Gavilá and 1 other author(s). DSD, page 428-435. IEEE, (2019)Energy proportionality in near-threshold computing servers and cloud data centers: Consolidating or Not?A. Pahlevan, Y. Qureshi, M. Zapater, A. Bartolini, D. Rossi, L. Benini, and D. Atienza. DATE, page 147-152. IEEE, (2018)A Product Engine for Energy-Efficient Execution of Binary Neural Networks Using Resistive Memories.J. Vieira, E. Giacomin, Y. Qureshi, M. Zapater, X. Tang, S. Kvatinsky, D. Atienza, and P. Gaillardon. VLSI-SoC, page 160-165. IEEE, (2019)

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Disambiguation of "Zapater, Marina"

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MAMUT: Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-User Video Transcoding.

Please choose a person to relate this publication to

Marina Maier

Marina Mikhaylova

Marina Tsoi

Marina Kopp

Marina Petrova

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Zapater, Marina"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML MAMUT: Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-User Video Transcoding.

Please choose a person to relate this publication to

Marina Maier

Marina Mikhaylova

Marina Tsoi

Marina Kopp

Marina Petrova

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

MAMUT: Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-User Video Transcoding.