نتائج البحث - "Haber, Tom"

Relation: Lecture Notes in Computer Science; 11536; Rodrigues, João M. F.; Cardoso, Pedro J. S.; Monteiro, Jânio; Lam, Roberto; Lees, Michael H.; Dongarra, Jack J.; Sloot, Peter M.A. (Ed.). Computational Science – ICCS 2019 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part I, SPRINGER INTERNATIONAL PUBLISHING AG, p. 628 -641; http://hdl.handle.net/1942/33064; 641; 628; WOS:000589288200046

الاتاحة: http://hdl.handle.net/1942/33064
https://doi.org/10.1007/978-3-030-22734-0_46

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9

Report

Ray-Based Reflectance Model for Diffraction

المؤلفون: Cuypers, Tom, Oh, Se Baek, Haber, Tom, Bekaert, Philippe, Raskar, Ramesh

مصطلحات موضوعية: Computer Science - Graphics

URL الوصول: http://arxiv.org/abs/1101.5490

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10

Book

From Conditional Independence to Parallel Execution in Hierarchical Models

المؤلفون: Nemeth, Balazs, Haber, Tom, Liesenborgs, Jori, Lamotte, Wim

المصدر: Lecture Notes in Computer Science ; Computational Science – ICCS 2020 ; page 161-174 ; ISSN 0302-9743 1611-3349 ; ISBN 9783030503703 9783030503710

الاتاحة: http://dx.doi.org/10.1007/978-3-030-50371-0_12
http://link.springer.com/content/pdf/10.1007/978-3-030-50371-0_12

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11

Conference

Reproducible Roulette Wheel Sampling for Message Passing Environments

المؤلفون: NEMETH, Balazs, HABER, Tom, LIESENBORGS, Jori, LAMOTTE, Wim

المساهمون: NEMETH, Balazs, HABER, Tom, LIESENBORGS, Jori, LAMOTTE, Wim

مصطلحات موضوعية: genetic algorithms, roulette wheel selection, sequential, Monte Carlo, HPC, message passing

وصف الملف: application/pdf

Relation: Lecture Notes in Computer Science; 10861; Shi, Yong; Fu, Haohuan; Tian, Yingjie; Krzhizhanovskaya, Valeria V.; Lees, Michael Harold; Dongarra, Jack; Sloot, Peter M. A. (Ed.). Computational Science – ICCS 2018, Springer,p. 799-805; http://hdl.handle.net/1942/26182; 805; 799

الاتاحة: http://hdl.handle.net/1942/26182
https://doi.org/10.1007/978-3-319-93701-4_63

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12

Conference

Improving ODE integration on graphics processing units by reducing thread divergence

المؤلفون: Kovac, Thomas, Haber, Tom, Van Reeth, Frank, Hens, Niel

المصدر: 0302-9743 ; Lecture notes in computer science

مصطلحات موضوعية: Mathematics, Biology, Computer. Automation

Relation: info:eu-repo/semantics/altIdentifier/isi/000589293800035

الاتاحة: https://hdl.handle.net/10067/1742980151162165141
https://repository.uantwerpen.be/docstore/d:irua:4144

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13

Academic Journal

Surgery-Guided Removal of Ovarian Cancer Using Up-Converting Nanoparticles

المؤلفون: Marotta, Christopher B., Haber, Tom, Berlin, Jacob M., Grubbs, Robert H.

المصدر: ACS Applied Materials & Interfaces, 12(43), 48371-48379, (2020-10-28)

مصطلحات موضوعية: ovarian cancer, silica coating, up-converting nanoparticles, near-IR, guided surgery, tumor removal

Relation: https://doi.org/10.1021/acsami.0c14983; https://www.ncbi.nlm.nih.gov/pmc/PMC8557954; eprintid:106184

الاتاحة: https://www.ncbi.nlm.nih.gov/pmc/PMC8557954
https://doi.org/10.1021/acsami.0c14983

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14

Conference

SW-SGD: The Sliding Window Stochastic Gradient Descent Algorithm

المؤلفون: Chakroun, Imen, Haber, Tom, Ashby, Thomas J.

مصطلحات موضوعية: SGD, sliding window, machine learning, SVM, logistic regression

وصف الملف: application/pdf

Relation: Procedia Computer Science; 108; info:eu-repo/grantAgreement/EC/H2020/671555; Koumoutsakos, Pedro; Lees, Michael; Krzhizhanovskaya, Valeria; Dongarra, Jack; Sloot, Peter M. A. (Ed.). International conference on computational science (ICCS 2017), Elsevier Science BV,p. 2318-2322; http://hdl.handle.net/1942/26396; 2322; 2318; 000404959000243

الاتاحة: http://hdl.handle.net/1942/26396
https://doi.org/10.1016/j.procs.2017.05.082

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Full Text Finder

15

Conference

Improving Operational Intensity in Data Bound Markov Chain Monte Carlo

المؤلفون: Nemeth, Balazs, Haber, Tom, Ashby, Thomas J., Lamotte, Wim

مصطلحات موضوعية: operational intensity, MCMC, Bayesian logistic regression, HPC, Big Data

وصف الملف: application/pdf

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In this paper, we present a literature survey of the latest advances in researches on machine learning for big data processing. First, we review the machine learning techniques and highlight some promising learning methods in recent studies, such as representation learning, deep learning, distributed and parallel learning, transfer learning, active learning, and kernel-based learning. Next, we focus on the analysis and discussions about the challenges and possible solutions of machine learning for big data. Following that, we investigate the close connections of machine learning with signal processing techniques for big data processing. Finally, we outline several open issues and research trends.", issn="1687-6180", doi="10.1186/s13634-016-0355-x", url="http://dx.doi.org/10.1186/s13634-016-0355-x" } @article{McVoy1996, title = {{lmbench: Portable Tools for Performance Analysis}}, year = {1996}, journal = {Proc. of the USENIX Annual Technical Conf.}, author = {McVoy, Larry and Staelin, Carl}, number = {January} } @article{Williams2009, title = {{Roofline: an insightful visual performance model for multicore architectures}}, year = {2009}, journal = {Communications of the ACM}, author = {Williams, Samuel and Waterman, Andrew and Patterson, David}, number = {4}, pages = {65–76}, volume = {52}, url = {www.eecs.berkeley.edu/~waterman/papers/roofline.pdf}, isbn = {0001-0782}, issn = {0001-0782} } @article{Wulf1995, title = {{Hitting the memory wall: Implications of the Obvious}}, year = {1995}, journal = {ACM SIGARCH Computer Architecture News}, author = {Wulf, Wm. a. and McKee, Sally a.}, pages = {20--24}, volume = {23}, isbn = {0163-5964}, issn = {01635964} } @book{P.Murphy2012a, title = {{Machine Learning: A Probabilistic Perspective}}, year = {2012}, booktitle = {Machine Learning: A Probabilistic Perspective}, author = {P. Murphy, Kevin}, url = {https://mitpress.mit.edu/books/machine-learning-0}, isbn = {9780262306164} }; 108; info:eu-repo/grantAgreement/EC/H2020/671555; Procedia Computer Science, 108(C), p. 2348-2352 (Art N° 205); http://hdl.handle.net/1942/23913; 2352; C; 2348; 000404959000249; http://www.sciencedirect.com/science/article/pii/S1877050917305252