Source: http://www.bbdc.berlin/publications/?tx_bib_pi1%5Byear%5D=all&cHash=cb726670830395943097c2207f381422
Timestamp: 2019-04-26 02:06:12+00:00

Document:
in Proc. 20th International Conference on Extending Database Technology (EDBT), March 21-24, 2017.
Addressing Hadoop's Small File Problem With an Appendable Archive File Format.
In the Proceedings of the Computing Frontiers Conference (CF).
Gupta, P.; Gramatke, A.; Einspanier, R.; Schütte, M.; von Kleist, M.; Sharbati, J.
In silico cytotoxicity assessment on cultured rat intestinal cells deduced from cellular impedance measurement.
Gornitz, N.; Lima, L. A.; Müller, K. R.; Kloft, M.; Nakajima, S.
Support Vector Data Descriptions and K-means Clustering: One Class?
Goldsmith, B. R.; Boley, M.; Vreeken, J.; Scheffler, M.; Ghiringhelli, L. M.
Uncovering structure-property relationships of materials by subgroup discovery.
Giotsas, V.; Smaragdakis, G.; Feldmann, A.; Berger, A.; Aben, E.
Detecting Peering Infrastructure Outages in the Wild.
Ghiringhelli, L. M.; Vybiral, J.; Ahmetcik, E.; Ouyang, R.; Levchenko,, S. V.; Draxl, C.; Scheffler, M.
Learning physical descriptors for materials science by compressed sensing.
Gelß, P.; Klus, S.; Matera, S.; Schütte, Ch.
Nearest-Neighbor Interaction Systems in the Tensor Train Format.
Feldmann, Anja; Hauswirth, M.; Markl, V.
Enabling Wide Area Data Analytics with CDPPs (Collaborative Distributed Processing Pipelines.
Deng, D.; Fernandez, R.; Abedjan, Z.; Wang, S.; Stonebraker, S.; Elmagarmid, A.; Ilyas, I.; Madden, S.; Ouzzani, M.; Tang, N.
Conrad, T.; Genzel, M.; Cvetkovic, N.; Wulkow, N.; Leichtle, A.; Vybiral, J.; Kutyniok, G.; Schütte, Ch.
Chmiela, S.; Tkatchenko, A.; Sauceda, H. E.; Poltavsky, I.; Schütt, K. T.; Müller, K.-R.
Brockherde, F.; Vogt, L.; Li, L.; Tuckerman, M. E.; Burke, K.; Müller, K. R.
Bosse, S.; Maniry, D.; Müller, K. R.; Wiegand, Th.; Samek, w.
Boley, M.; Goldsmith, B.; Ghiringhelli, L.; Vreeken, J.
Identifying Consistent Statements about Numerical Data with Dispersion-Corrected Subgroup Discovery.
Boden, Ch.; Spina, A.; Rabl, T.; Markl, V.
Benchmarking Data Flow Systems for Scalable Machine Learning.
Post-Debugging in Large Scale Analytic Systems.
In: Datenbanksysteme für Business, Technologie und Web (BTW), Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS) , page 65-72.
Why Does a Hilbertian Metric Work Efficiently in Online Learning With Kernels?
When to Use a Distributed Dataflow Engine: Evaluating the Performance of Apache Flink.
Selecting Resources for Distributed Dataflow Systems According to Runtime Targets.
In the Proceddings of IEEE 35th International Performance Computing and Communications Conference (IPCCC).
Continuously Improving the Resource Utilization of Iterative Parallel Dataflows.
In the Proceedings of the IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW). Presented at the International Workshop on Big Data and Cloud Performance (DCPerf). IEEE.
Visually Programming Dataflows for Distributed Data Analytics.
In the Proceddings of IEEE International Conference on Big Data (Big Data).
Sannelli, C.; Vidaurre, C.; Müller, K. R.; Blankertz, B.
Ensembles of adaptive spatial filters increase BCI performance: an online evaluation.
Samek, Wojciech; Blythe, Duncan A. J.; Curio, Gabriel; Müller, Klaus-Robert; Blankertz, Benjamin; Nikulin, Vadim V.
CoLoc: Distributed Data and Container Colocation for Data-Intensive Applications.
. In the Proceddings of IEEE International Conference on Big Data (Big Data).
Sharing Hash Codes for Multiple Purpose.
Nakajima, S.; Tomioka, R.; Sugiyama, M.; Babacan, S. D.
Min, B. K.; Dähne, S.; Ahn, M. H.; Noh, Y. K.; Müller, K. R.
Decoding of top-down cognitive processing for SSVEP-controlled BMI.
Lapuschkin, S.; Binder, A.; Montavon, G.; Müller, K. R.; Samek, w.
Analyzing classifiers: fisher vectors and deep neural networks.
In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , page 2912-2920.
Krause, S.; Xu, F.; Uszkoreit, H.; Weißenborn, D.
Event Linking with Sentential Features from Convolutional Neural Networks.
Sar-graphs: A language resource connecting linguistic knowledge with semantic relations from knowledge graphs.
Koltai, P.; Ciccotti, G.; Schütte, Ch.
On Markov state models for non-equilibrium molecular dynamics.
Jugel, U.; Jerzak, Z.; Markl, V.
Big data on a few pixels.
In: IEEE International Conference on Big Data (Big Data) , page 895-900.
Jugel, U.; Jerzak, Z.; Hackenbroich, G.; Markl, V.
Aura: A Flexible Dataflow Engine for Scalable Data Processing.
in Andreas Knüpfer, Tobias Hilbrich, Christoph Niethammer, José Gracia, Wolfgang E. Nagel, Michael M. Resch (eds.), Tools for High Performance Computing 2015. Springer.
Hennig, L.; Thomas, Ph.; Ai, R.; Kirschnick, J.; Wang, H.; Pannier, J.; Zimmermann, N.; Schmeier, S.; Xu, F.; Ostwald, J.; Uszkoreit, H.
Real-Time Discovery and Geospatial Visualization of Mobility and Industry Events from Large-Scale, Heterogeneous Data Streams.
Gül, S.; Meyer, J. T.; Hellge, C.; Schierl, Th.; Samek, w.
Hybrid Video Object Tracking in H.265/HEVC Video Streams.
Ghiringhelli, L. M.; Carbogno, C.; Levchenko, S.; Mohamed, F.; Huhs, G.; Lueders, M.; Oliveira, M.; Scheffler,, M.
Towards a Common Format for Computational Materials Science Data.
Relation- and phrase-level linking of FrameNet with Sar-graphs.
Kraken: Online and Elastic Resource Reservations for Multitenant Datacenters.
Proc. 35th IEEE Conference on Computer Communications (INFOCOM).
Fajerski, J.; Noack, M.; Reinefeld, A.; Schintke, F.; Steinke, Th.
Fast In-Memory Checkpointing with POSIX API for Legacy Exascale-Applications.
TEG-REP: A corpus of Textual Entailment Graphs based on Relation Extraction Patterns.
Bosse, S.; Maniry, D.; Wiegand, Th.; Samek, w.
A Deep Neural Network for Image Quality Assessment.
In: Proceedings of the IEEE International Conference on Image Processing (ICIP) , page 3773-77.
Bosse, S.; Maniry, D.; Müller, K.-R.; Wiegand, Th.; Samek, w.
Neural Network-Based Full-Reference Image Quality Assessment.
In: Proceedings of the Picture Coding Symposium (PCS), 1-5 , page 3773-77.
Bosse, S.; Chen, Q.; Siekmann, M.; Samek, w.; Wiegand, Th.
Shearlet-based reduced reference image quality assessment.
Bauer, Alexander; Nakajima, Shinichi; Müller, K. R.
Efficient Exact Inference With Loss Augmented Objective in Structured Learning.
IEEE transactions on neural networks and learning systems Volume PP, no. 99 , page 1 - 14.
In: German Conference on Pattern Recognition , page 344 - 354.
Alexandrov, A.; Salzmann, A.; Krastev, G.; Katsifodimos, A.; Markl, V.
Emma in Action: Declarative Dataflows for Scalable Data Analysis.
In: SIGMOD Volume Record 45(1) , page 51-58.
Abedjan, Z.:; Chu,, X.; Deng, D.; Fernandez, R.; Ilyas, R.; Ouzzani, I.; Papotti, M.; Stonebraker, M.; Tang, N.
In: 53nd Annual Meeting of the Association for Computational Linguistics, ACL , page 596-605.
In: ADMS@VLDB, 2015. , page 1-12.
Network-Aware Resource Management for Scalable Data Analytics Frameworks.
In Proceedings of the First Workshop on Data-Centric Infrastructure for Big Data Science (DIBS) 2015, co-located with the 2015 IEEE International Conference on BigData (BigData). IEEE.
Reinefeld, A.; Schütt, Ch.; Döbbelin, R.
Fast Memory Access for Data Intensive Applications.
Annoyed Users: Ads and Ad-Block Usage in the Wild.
Nakajima, S.; Tomioka, R.; Sugiyama, M.; Babacan, S.D.
In: IEEE 35th International Conference on Distributed Computing Systems (ICDCS) , page 399-410.
Improvement of n-ary Relation Extraction by Adding Lexical Semantics to Distant-Supervision Rule Learning.
Sar-graphs: A Linked Linguistic Knowledge Resource Connecting Facts with Language.
Learning a Distributed Representation for Event Patterns.
A Web-based Collaborative Evaluation Tool for Automatically Learned Relation Extraction Patterns.
Hansen, S.T.; Winkler, I.; Hansen, L.K.; Müller, K.-R.; Dähne, S.
In International Workshop on Pattern Recognition in Neuroimaging, 2015. IEEE.
Ghiringhelli, L.M.; Vybiral, J.; Levchenko, S.V.; Draxl, C.; Scheffler, M.
Optimistic Recovery for Iterative Dataflows in Action.
In Proceedings of the 2015 ACM SIGMOD International conference on Management of Data (SIGMOD '15).
Djurdjevac, C.; Banisch, R.; Schütte, Ch.
Modularity of Directed Networks: Cycle Decomposition Approach.
Dähne, S.; Goltz, D.; Gundlach, C.; Mehnert, J.; Villringer, A.; Haufe, S.; Müller, K.-R.
In Annual Meeting of the Organization for Human Brain Mapping (OHBM).
Carbone, P.; Katsifodimos, A.; Ewen, St.; Markl, V.; Haridi, S.; Tzoumas, K.
Apache Flink™: Stream and Batch Processing in a Single Engine.
Bhattacharya, S.; Sonin, B.; Jumonville, C.J.; Ghiringhelli, L.M.; Marom, N.
Computational Design of Nanoclusters by Property-Based Genetic Algorithms: Tuning the Electronic Properties of (TiO2)n Clusters.
Towards a Taxonomy for Error Management in Big Data Analytics Systems.
IEEE Transactions on Neural Networks and Learning Systems. Volume 28(1) , page 44-45.
Bach, S.; Binder, A.; Montavon, G.; Klauschen, F.; Müller, K.-R.; Samek, w.
In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data (SIGMOD '15).
Nakajima, S.; Sato, I.; Sugiyama, M.; Watanabe, K.; Kobayashi, H.
Twenty-Eighth Annual Conference on Neural Information Processing Systems (NIPS2014).
Bauer, A.; Gornitz, N.; Biegler, F.; Müller, K.-R.; Kloft, M.
Efficient algorithms for exact inference in sequence labeling SVMs.

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