Publications

Found 4258 results
Author [ Title(Desc)] Type Year
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M
Feldman, J. (1979).  Is Memory Still a Mystery?. Proceedings of the Cold Spring Harbor Symposium on Models of Specific Systems.
Wang, K., Kellman M., Sandino C. M., Zhang K., Vasanawala S. S., Tamir J. I., et al. (2021).  Memory-efficient Learning for High-Dimensional MRI Reconstruction. Proceedings of International Society for Magnetic Resonance in Medicine.
Bourlard, H., & Morgan N. (1989).  Merging Multilayer Perceptrons and Hidden Markov Models: Some Experiments in Continuous Speech Recognition.
Bourlard, H., & Morgan N. (1989).  Merging Multilayer Perceptrons & Hidden Markov Models: Some Experiments in Continuous Speech Recognition.
Bourlard, H., & Morgan N. (1990).  Merging Multilayer Perceptrons & Hidden Markov Models: Some Experiments in Continuous Speech Recognition.
Fillmore, C. J. (2008).  The Merging of "Frames". 1-12.
Hindman, B., Konwinski A., Zaharia M., Ghodsi A., Joseph A. D., Katz R. H., et al. (2011).  Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center. 1-14.
Hindman, B., Konwinski A., Zaharia M., Ghodsi A., Joseph A. D., Katz R. H., et al. (2010).  Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center.
Hindman, B., Konwinski A., Zaharia M., Ghodsi A., Joseph A. D., Katz R. H., et al. (2011).  Mesos: Flexible Resource Sharing for the Cloud. USENIX ;login:. 36(4), 37-45.
Günther, O., & Voisard A. (1996).  Metadata in Geographic and Environmental Data Management.
Petruck, M. R. L. (2018).  MetaNet,. Benjamins’ Current Trends #100.
Petruck, M. R. L. (2016).  MetaNet, Special Issue of Constructions and Frames: 8.2. 8(2), 
Petruck, M. R. L., & Dodge E. (2016).  MetaNet Tutorial. Proceedings of ACL 2016.
Moskewicz, M. W., Jannesari A., & Keutzer K. (2016).  A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications. arXiv preprint arXiv:1611.06945.
Jung, V. (1999).  MetaViz: Visual Interaction with Geospatial Digital Libraries.
Alt, H., Guibas L. J., Mehlhorn K., & Karp R. M. (1996).  A Method for Obtaining Randomized Algorithms with Small Tail Probabilities. Algorithmica. 16(4-5), 543-547.
Alt, H., Guibas L. J., Mehlhorn K., Karp R. M., & Wigderson A. (1991).  A Method for Obtaining Randomized Algorithms with Small Tail Probabilities.
Bouillon, P., Chatzichrisafis N., Hockey B. Ann, Rayner M., Santaholma M., Starlander M., et al. (2005).  A Methodology for Comparing Grammar-Based and Robust Approaches to Speech Understanding. Proceedings of the 9th European Conference on Speech Communication and Technology (Interspeech 2005-Eurospeech 2005). 1877-1880.
Tschantz, M. Carl, Datta A., Datta A., & Wing J. M. (2015).  A Methodology for Information Flow Experiments. 2015 IEEE 28th Computer Security Foundations Symposium. 554-568.
Yago, C.. M., Ruiz P. M., & Gómez-Skarmeta A. (2005).  Metodo de Eliminacion de Reenvios Basado en Contador y Adaptable a la Movilidad para Reducir la Sobrecarga de Datos al Encaminar. Proceedings of the V Jornadas de Ingenieria Telematica.
Ladkin, P. (1989).  Metric Constraint Satisfaction with Intervals.
Taylor, M.. E., Kulis B., & Sha F.. (2011).  Metric Learning for Reinforcement Learning Agents.
Rozov, R., Halperin E., & Shamir R. (2012).  MGMR: Leveraging RNA-Seq Population Data to Optimize Expression Estimation. 13,
Puder, A., & Römer K. (1998).  MICO: A CORBA 2.2 Compliant Implementation.
Weaver, N. (2021).  The Microsoft Exchange Hack and the Great Email Robbery.

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