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261.
Buch
Optimization for Machine Learning. MIT Press, Cambridge, MA, USA (2011), 494 S.
262.
Buch
Handbook of Statistical Bioinformatics. Springer, Berlin, Germany (2011), IX,627 S.
Buchkapitel (9)
263.
Buchkapitel
Projected Newton-type methods in machine learning. In: Optimization for Machine Learning, S. 305 - 330 (Hg. Sra, S.; Nowozin, S.; Wright, S. J.). MIT Press, Cambridge, MA, USA (2011)
264.
Buchkapitel
Statistical Learning Theory: Models, Concepts, and Results. In: Handbook of the History of Logic Vol. 10: Inductive Logic, S. 651 - 706 (Hg. Gabbay; M., D.; Woods; J.; Hartmann et al.). Elsevier North Holland, Amsterdam, Netherlands (2011)
265.
Buchkapitel
Benchmark datasets for pose estimation and tracking. In: Visual Analysis of Humans: Looking at People, S. 253 - 274 (Hg. Moeslund, T. B.; Hilton, A.; Krüger, V.; Sigal, L.). Springer, London (2011)
266.
Buchkapitel
Kernel Methods in Bioinformatics. In: Handbook of Statistical Bioinformatics, S. 317 - 33 (Hg. Lu Schölkopf B., H. H.-S.; Zhao, H.). Springer, Berlin (2011)
267.
Buchkapitel
Machine Learning Methods for Automatic Image Colorization. In: Computational Photography: Methods andApplications, S. 395 - 418 (Hg. Lukac, R.). CRC Press, Boca Raton, FL, USA (2011)
268.
Buchkapitel
Core–Shell Nanocrystals. In: Comprehensive Nanoscience and Technology. Vol. 1, S. 272 - 287 (Hg. Andrews, D.L.; Scholes, G.D.; Wiederrecht, G.P.). Elsevier B.V. (2011)
269.
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Robot Learning. In: Encyclopedia of Machine Learning, S. 865 - 869 (Hg. Sammut; C.; Webb; I., G.). Springer, New York, NY, USA (2011)
270.
Buchkapitel
Field of experts. In: Markov Random Fields for Vision and Image Processing, S. 297 - 310 (Hg. Blake, A.; Kohli, P.; Rother, C.). MIT Press, Cambridge, Mass. [et al.] (2011)
271.
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Steerable random fields for image restoration and inpainting. In: Markov Random Fields for Vision and Image Processing, S. 377 - 387 (Hg. Blake, A.; Kohli, P.; Rother, C.). MIT Press, Cambridge, Mass. [et al.] (2011)
Konferenzband (2)
272.
Konferenzband
1). Twelfth European Powder Diffraction Conference (EPDIC 12), Darmstadt, 27. August 2010 - 30. August 2010. Odenbourg Wissenschaftverlag, München (2011), 492 S.
Proceedings of the Twelfth European Powder Diffraction Conference (Zeitschrift für Kristallographie Proceedings, 273.
Konferenzband
Vol. 19). COLT 2011. 24th Annual Conference on Learning Theory, Budapest [Hungary], 09. Juli 2011 - 11. Juli 2011. MIT Press, Cambridge, MA (2011), 834 S.
COLT 2011, 24th Annual Conference on Learning Theory- (JMLR: Workshop and Conference Proceedings, Konferenzbeitrag (84)
274.
Konferenzbeitrag
Information, learning and falsification. In: NIPS 2011 Philosophy and Machine Learning Workshop, S. 1 - 4. NIPS 2011 Philosophy and Machine Learning Workshop, Sierra Nevada, 17. Dezember 2011. (2011)
275.
Konferenzbeitrag
On the discardability of data in Support Vector Classification problems. In: 50th IEEE Conference on Decision and Control and European Control Conference (CDC - ECC 2011), S. 3210 - 3215. (2011)
276.
Konferenzbeitrag
Statistical estimation for optimization problems on graphs. In: NIPS Workshop on Discrete Optimization in Machine Learning (DISCML) 2011: Uncertainty, Generalization and Feedback, S. 1 - 6. (2011)
277.
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20, S. 181 - 196 (2011)
Learning low-rank output kernels. 3rd Asian Conference on Machine Learning (ACML 2011), Taoyuan, Taiwan. JMLR: Workshop and Conference Proceedings 278.
Konferenzbeitrag
Fast removal of non-uniform camera shake. In: 13th IEEE International Conference on Computer Vision (ICCV 2011), S. 463 - 470. (2011)
279.
Konferenzbeitrag
Non-stationary correction of optical aberrations. In: 13th IEEE International Conference on Computer Vision (ICCV 2011), S. 659 - 666. (2011)
280.
Konferenzbeitrag
A general linear non-Gaussian state-space model: Identifiability, identification, and applications. In: 3rd Asian Conference on Machine Learning (ACML 2011), S. 113 - 128. (2011)