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