99 Publications

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[99]
2019 | Book (Editor) | IST-REx-ID: 7171
K. Kersting, C. Lampert, and C. Rothkopf, Eds., Wie Maschinen lernen. Springer Nature, 2019.
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[98]
2019 | Journal Article | IST-REx-ID: 6554   OA
Y. Xian, C. Lampert, B. Schiele, and Z. Akata, “Zero-shot learning - A comprehensive evaluation of the good, the bad and the ugly,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 9, pp. 2251–2265, 2019.
View | DOI | Download (ext.) | arXiv
 
[97]
2019 | Conference Paper | IST-REx-ID: 6942   OA
P. Ashok, T. Brázdil, K. Chatterjee, J. Křetínský, C. Lampert, and V. Toman, “Strategy representation by decision trees with linear classifiers,” in 16th International Conference on Quantitative Evaluation of Systems, Glasgow, United Kingdom, 2019, vol. 11785, pp. 109–128.
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[96]
2019 | Conference Paper | IST-REx-ID: 6569   OA
P. Bui Thi Mai and C. Lampert, “Towards understanding knowledge distillation,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, United States, 2019, vol. 97, pp. 5142–5151.
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[95]
2019 | Conference Paper | IST-REx-ID: 6590   OA
N. H. Konstantinov and C. Lampert, “Robust learning from untrusted sources,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, USA.
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[94]
2019 | Conference Paper | IST-REx-ID: 6482
R. Sun and C. Lampert, “KS(conf): A light-weight test if a ConvNet operates outside of Its specifications,” presented at the GCPR: Conference on Pattern Recognition, Stuttgart, Germany, 2019, vol. 11269, pp. 244–259.
View | Files available | DOI | Download (ext.) | arXiv
 
[93]
2019 | Journal Article | IST-REx-ID: 6944   OA
R. Sun and C. Lampert, “KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications,” International Journal of Computer Vision, 2019.
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[92]
2018 | Journal Article | IST-REx-ID: 321
T. Darrell, C. Lampert, N. Sebe, Y. Wu, and Y. Yan, “Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, pp. 1029–1031, 2018.
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[91]
2018 | Conference Paper | IST-REx-ID: 6011   OA
I. Kuzborskij and C. Lampert, “Data-dependent stability of stochastic gradient descent,” in Proceedings of the 35 th International Conference on Machine Learning, Stockholm, Sweden, 2018, vol. 80, pp. 2815–2824.
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[90]
2018 | Conference Paper | IST-REx-ID: 6012   OA
S. Sahoo, C. Lampert, and G. S. Martius, “Learning equations for extrapolation and control,” in Proceedings of the 35th International Conference on Machine Learning, Stockholm, Sweden, 2018, vol. 80, pp. 4442–4450.
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[89]
2017 | Conference Paper | IST-REx-ID: 911   OA
A. Royer, A. Kolesnikov, and C. Lampert, “Probabilistic image colorization,” presented at the BMVC: British Machine Vision Conference, London, United Kingdom.
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[88]
2017 | Conference Paper | IST-REx-ID: 1000   OA
A. Kolesnikov and C. Lampert, “PixelCNN models with auxiliary variables for natural image modeling,” presented at the ICML: International Conference on Machine Learning, Sydney, Australia, 2017, vol. 70, pp. 1905–1914.
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[87]
2017 | Conference Paper | IST-REx-ID: 6841   OA
G. S. Martius and C. Lampert, “Extrapolation and learning equations,” in 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings, Toulon, France, 2017.
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[86]
2017 | Conference Paper | IST-REx-ID: 998   OA
S. A. Rebuffi, A. Kolesnikov, G. Sperl, and C. Lampert, “iCaRL: Incremental classifier and representation learning,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 5533–5542.
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[85]
2017 | Conference Paper | IST-REx-ID: 999   OA
A. Pentina and C. Lampert, “Multi-task learning with labeled and unlabeled tasks,” presented at the ICML: International Conference on Machine Learning, Sydney, Australia, 2017, vol. 70, pp. 2807–2816.
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[84]
2017 | Conference Paper | IST-REx-ID: 1108   OA
A. Zimin and C. Lampert, “Learning theory for conditional risk minimization,” presented at the AISTATS: Artificial Intelligence and Statistics, Fort Lauderdale, FL, United States, 2017, vol. 54, pp. 213–222.
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[83]
2017 | Conference Paper | IST-REx-ID: 750
J. Pielorz, M. Prandtstetter, M. Straub, and C. Lampert, “Optimal geospatial volunteer allocation needs realistic distances,” in 2017 IEEE International Conference on Big Data, Boston, MA, United States, 2017, pp. 3760–3763.
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[82]
2016 | Conference Paper | IST-REx-ID: 1369   OA
A. Kolesnikov and C. Lampert, “Seed, expand and constrain: Three principles for weakly-supervised image segmentation,” presented at the ECCV: European Conference on Computer Vision, Amsterdam, The Netherlands, 2016, vol. 9908, pp. 695–711.
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[81]
2016 | Conference Paper | IST-REx-ID: 1707
J. Pielorz and C. Lampert, “Optimal geospatial allocation of volunteers for crisis management,” presented at the ICT-DM: Information and Communication Technologies for Disaster Management, Rennes, France, 2016.
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[80]
2016 | Conference Paper | IST-REx-ID: 1102   OA
A. Kolesnikov and C. Lampert, “Improving weakly-supervised object localization by micro-annotation,” in Proceedings of the British Machine Vision Conference 2016, York, United Kingdom, 2016, vol. 2016–September, p. 92.1-92.12.
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[79]
2015 | Conference Paper | IST-REx-ID: 1857   OA
A. Pentina, V. Sharmanska, and C. Lampert, “Curriculum learning of multiple tasks,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 5492–5500.
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[78]
2015 | Conference Paper | IST-REx-ID: 1858   OA
C. Lampert, “Predicting the future behavior of a time-varying probability distribution,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 942–950.
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[77]
2015 | Conference Paper | IST-REx-ID: 1860   OA
A. Royer and C. Lampert, “Classifier adaptation at prediction time,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 1401–1409.
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[76]
2015 | Conference Paper | IST-REx-ID: 1859   OA
N. Shah, V. Kolmogorov, and C. Lampert, “A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA, 2015, pp. 2737–2745.
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[75]
2015 | Conference Paper | IST-REx-ID: 1425   OA
A. Pentina and C. Lampert, “Lifelong learning with non-i.i.d. tasks,” presented at the NIPS: Neural Information Processing Systems, Montreal, Canada, 2015, vol. 2015, pp. 1540–1548.
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[74]
2014 | Conference Paper | IST-REx-ID: 2171   OA
A. Kolesnikov, M. Guillaumin, V. Ferrari, and C. Lampert, “Closed-form approximate CRF training for scalable image segmentation,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Zurich, Switzerland, 2014, vol. 8691, no. PART 3, pp. 550–565.
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[73]
2014 | Conference Paper | IST-REx-ID: 2033   OA
D. Hernandez Lobato, V. Sharmanska, K. Kersting, C. Lampert, and N. Quadrianto, “Mind the nuisance: Gaussian process classification using privileged noise,” in Advances in Neural Information Processing Systems, Montreal, Canada, 2014, vol. 1, no. January, pp. 837–845.
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[72]
2014 | Conference Paper | IST-REx-ID: 2172
V. Sydorov, M. Sakurada, and C. Lampert, “Deep Fisher Kernels – End to end learning of the Fisher Kernel GMM parameters,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Columbus, USA, 2014, pp. 1402–1409.
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[71]
2014 | Conference Paper | IST-REx-ID: 2160   OA
A. Pentina and C. Lampert, “A PAC-Bayesian bound for Lifelong Learning,” presented at the ICML: International Conference on Machine Learning, Beijing, China, 2014, vol. 32, pp. 991–999.
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[70]
2014 | Conference Paper | IST-REx-ID: 2173   OA
S. Khamis and C. Lampert, “CoConut: Co-classification with output space regularization,” in Proceedings of the British Machine Vision Conference 2014, Nottingham, UK, 2014.
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[69]
2014 | Book Chapter | IST-REx-ID: 1829
K. Muelling, O. Kroemer, C. Lampert, and B. Schölkopf, “Movement templates for learning of hitting and batting,” in Learning Motor Skills, vol. 97, J. Kober and J. Peters, Eds. Springer, 2014, pp. 69–82.
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[68]
2013 | Conference Paper | IST-REx-ID: 2948   OA
T. Tommasi, N. Quadrianto, B. Caputo, and C. Lampert, “Beyond dataset bias: Multi-task unaligned shared knowledge transfer,” vol. 7724. Springer, pp. 1–15, 2013.
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[67]
2013 | Encyclopedia Article | IST-REx-ID: 3321
N. Quadrianto and C. Lampert, “Kernel based learning,” in Encyclopedia of Systems Biology, vol. 3, W. Dubitzky, O. Wolkenhauer, K. Cho, and H. Yokota, Eds. Springer, 2013, pp. 1069–1069.
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[66]
2013 | Conference Paper | IST-REx-ID: 2901   OA
C. Chen, V. Kolmogorov, Z. Yan, D. Metaxas, and C. Lampert, “Computing the M most probable modes of a graphical model,” presented at the AISTATS: Conference on Uncertainty in Artificial Intelligence, Scottsdale, AZ, United States, 2013, vol. 31, pp. 161–169.
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[65]
2013 | Conference Paper | IST-REx-ID: 2293   OA
V. Sharmanska, N. Quadrianto, and C. Lampert, “Learning to rank using privileged information,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013, pp. 825–832.
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[64]
2013 | Journal Article | IST-REx-ID: 2516
C. Lampert, H. Nickisch, and S. Harmeling, “Attribute-based classification for zero-shot learning of object categories,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 3, pp. 453–465, 2013.
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[63]
2013 | Conference Paper | IST-REx-ID: 2294   OA
T. Kazmar, E. Kvon, A. Stark, and C. Lampert, “Drosophila Embryo Stage Annotation using Label Propagation,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013.
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[62]
2012 | Conference Paper | IST-REx-ID: 3124
F. Korc, V. Kolmogorov, and C. Lampert, “Approximating marginals using discrete energy minimization,” presented at the ICML: International Conference on Machine Learning, Edinburgh, Scotland, 2012.
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[61]
2012 | Technical Report | IST-REx-ID: 5396   OA
F. Korc, V. Kolmogorov, and C. Lampert, Approximating marginals using discrete energy minimization. IST Austria, 2012.
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[60]
2012 | Conference Paper | IST-REx-ID: 3125
V. Sharmanska, N. Quadrianto, and C. Lampert, “Augmented attribute representations,” presented at the ECCV: European Conference on Computer Vision, Florence, Italy, 2012, vol. 7576, no. PART 5, pp. 242–255.
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[59]
2012 | Conference Paper | IST-REx-ID: 2825
C. Lampert, “Dynamic pruning of factor graphs for maximum marginal prediction,” presented at the NIPS: Neural Information Processing Systems, Lake Tahoe, NV, United States, 2012, vol. 1, pp. 82–90.
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[58]
2012 | Conference Paper | IST-REx-ID: 3126
A. Müller, S. Nowozin, and C. Lampert, “Information theoretic clustering using minimal spanning trees,” presented at the DAGM: German Association For Pattern Recognition, Graz, Austria, 2012, vol. 7476, pp. 205–215.
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[57]
2012 | Journal Article | IST-REx-ID: 3164
M. Blaschko and C. Lampert, “Guest editorial: Special issue on structured prediction and inference,” International Journal of Computer Vision, vol. 99, no. 3, pp. 257–258, 2012.
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[56]
2012 | Conference Paper | IST-REx-ID: 2915
O. Kroemer, C. Lampert, and J. Peters, “Multi-modal learning for dynamic tactile sensing,” 2012.
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[55]
2012 | Conference Paper | IST-REx-ID: 3127   OA
N. Quadrianto, C. Lampert, and C. Chen, “The most persistent soft-clique in a set of sampled graphs,” in Proceedings of the 29th International Conference on Machine Learning, Edinburgh, United Kingdom, 2012, pp. 211–218.
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[54]
2012 | Journal Article | IST-REx-ID: 3248   OA
C. Lampert and J. Peters, “Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components,” Journal of Real-Time Image Processing, vol. 7, no. 1, pp. 31–41, 2012.
View | Files available | DOI
 
[53]
2011 | Conference Paper | IST-REx-ID: 3319
N. Quadrianto and C. Lampert, “Learning multi-view neighborhood preserving projections,” presented at the ICML: International Conference on Machine Learning, Bellevue, USA, 2011, pp. 425–432.
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[52]
2011 | Conference Paper | IST-REx-ID: 3163
C. Lampert, “Maximum margin multi-label structured prediction,” presented at the NIPS: Neural Information Processing Systems, Granada, Spain, 2011.
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[51]
2011 | Conference Poster | IST-REx-ID: 3322
C. Lampert, Maximum margin multi label structured prediction. Neural Information Processing Systems, 2011.
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[50]
2011 | Journal Article | IST-REx-ID: 3389
M. Blaschko, J. Shelton, A. Bartels, C. Lampert, and A. Gretton, “Semi supervised kernel canonical correlation analysis with application to human fMRI,” Pattern Recognition Letters, vol. 32, no. 11, pp. 1572–1583, 2011.
View | DOI
 
[49]
2011 | Technical Report | IST-REx-ID: 5386   OA
C. Chen, D. Freedman, and C. Lampert, Enforcing topological constraints in random field image segmentation. IST Austria, 2011.
View | Files available | DOI
 
[48]
2011 | Conference Paper | IST-REx-ID: 3336
C. Chen, D. Freedman, and C. Lampert, “Enforcing topological constraints in random field image segmentation,” in CVPR: Computer Vision and Pattern Recognition, Colorado Springs, CO, USA, 2011, pp. 2089–2096.
View | Files available | DOI
 
[47]
2011 | Journal Article | IST-REx-ID: 3320
S. Nowozin and C. Lampert, “Structured learning and prediction in computer vision,” Foundations and Trends in Computer Graphics and Vision, vol. 6, no. 3–4, pp. 185–365, 2011.
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[46]
2011 | Journal Article | IST-REx-ID: 3382
O. Kroemer, C. Lampert, and J. Peters, “Learning dynamic tactile sensing with robust vision based training,” IEEE Transactions on Robotics, vol. 27, no. 3, pp. 545–557, 2011.
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[45]
2011 | Conference Paper | IST-REx-ID: 3337
Z. Wang, C. Lampert, K. Mülling, B. Schölkopf, and J. Peters, “Learning anticipation policies for robot table tennis,” presented at the IROS: RSJ International Conference on Intelligent Robots and Systems, San Francisco, USA, 2011, pp. 332–337.
View | DOI
 
[44]
2010 | Conference Paper | IST-REx-ID: 3794
C. Lampert and O. Krömer, “Weakly-paired maximum covariance analysis for multimodal dimensionality reduction and transfer learning,” presented at the ECCV: European Conference on Computer Vision, Heraklion, Crete, Greece, 2010, vol. 6312, pp. 566–579.
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[43]
2010 | Journal Article | IST-REx-ID: 3686
S. Nowozin and C. Lampert, “Global interactions in random field models: A potential function ensuring connectedness,” SIAM Journal on Imaging Sciences, vol. 3, no. 4 (Special Section on Optimization in Imaging Sciences), pp. 1048–1074, 2010.
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[42]
2010 | Conference Paper | IST-REx-ID: 3713
C. Lampert, “An efficient divide-and-conquer cascade for nonlinear object detection,” presented at the CVPR: Computer Vision and Pattern Recognition, 2010, pp. 1022–1029.
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[41]
2010 | Conference Paper | IST-REx-ID: 3682
K. Tang, M. Tappen, R. Sukthankar, and C. Lampert, “Optimizing one-shot recognition with micro-set learning,” presented at the CVPR: Computer Vision and Pattern Recognition, 2010, pp. 3027–3034.
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[40]
2010 | Conference Paper | IST-REx-ID: 3702
J. Kober, K. Mülling, O. Krömer, C. Lampert, B. Schölkopf, and J. Peters, “Movement templates for learning of hitting and batting,” presented at the ICRA: International Conference on Robotics and Automation, 2010, pp. 853–858.
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[39]
2010 | Conference Paper | IST-REx-ID: 3676
J. Wanke, A. Ulges, C. Lampert, and T. Breuel, “Topic models for semantic video compression,” presented at the MIR: Multimedia Information Retrieval, 2010, pp. 275–284.
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[38]
2010 | Conference Paper | IST-REx-ID: 3793
S. Nowozin, P. Gehler, and C. Lampert, “On parameter learning in CRF-based approaches to object class image segmentation,” presented at the ECCV: European Conference on Computer Vision, Heraklion, Crete, Greece, 2010, vol. 6316, pp. 98–111.
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[37]
2010 | Journal Article | IST-REx-ID: 3697
T. Tuytelaars, C. Lampert, M. Blaschko, and W. Buntine, “Unsupervised object discovery: A comparison,” International Journal of Computer Vision, vol. 88, no. 2, pp. 284–302, 2010.
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[36]
2009 | Conference Poster | IST-REx-ID: 3699
M. Blaschko, C. Lampert, and A. Bartels, Semi-supervised analysis of human fMRI data. Berlin Institute of Technology, 2009.
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[35]
2009 | Book | IST-REx-ID: 3707
C. Lampert, Kernel methods in computer vision, vol. 4. now, 2009, pp. 193–285.
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[34]
2009 | Conference Paper | IST-REx-ID: 3690
P. Dhillon, S. Nowozin, and C. Lampert, “Combining appearance and motion for human action classification in videos,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, no. 174, pp. 22–29.
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[33]
2009 | Conference Paper | IST-REx-ID: 3703
M. Blaschko and C. Lampert, “Object localization with global and local context kernels,” presented at the BMVC: British Machine Vision Conference, 2009, pp. 1–11.
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[32]
2009 | Conference Paper | IST-REx-ID: 3708
S. Nowozin and C. Lampert, “Global connectivity potentials for random field models,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 818–825.
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[31]
2009 | Journal Article | IST-REx-ID: 3710
C. Lampert, M. Blaschko, and T. Hofmann, “Efficient subwindow search: A branch and bound framework for object localization,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 12, pp. 2129–2142, 2009.
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[30]
2009 | Conference Paper | IST-REx-ID: 3715
C. Lampert and J. Peters, “Active structured learning for high-speed object detection,” presented at the DAGM: German Association For Pattern Recognition, 2009, vol. 5748, pp. 221–231.
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[29]
2009 | Journal Article | IST-REx-ID: 3696
C. Lampert and M. Blaschko, “Structured prediction by joint kernel support estimation,” Machine Learning, vol. 77, no. 2–3, pp. 249–269, 2009.
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[28]
2009 | Conference Paper | IST-REx-ID: 3704
C. Lampert, H. Nickisch, and S. Harmeling, “Learning to detect unseen object classes by between-class attribute transfer,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 951–958.
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[27]
2009 | Conference Paper | IST-REx-ID: 3709
C. Lampert, “Detecting objects in large image collections and videos by efficient subimage retrieval,” presented at the ICCV: International Conference on Computer Vision, 2009, pp. 987–994.
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[26]
2009 | Conference Paper | IST-REx-ID: 3711
P. Dhillon, S. Nowozin, and C. Lampert, “Combining appearance and motion for human action classification in videos,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 22–29.
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[25]
2009 | Conference Poster | IST-REx-ID: 3717
C. Lampert and J. Peters, A high-speed object tracker from off-the-shelf components. IEEE, 2009.
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[24]
2008 | Conference Paper | IST-REx-ID: 3698
M. Blaschko, C. Lampert, and A. Gretton, “Semi-supervised Laplacian regularization of kernel canonical correlation analysis,” presented at the ECML: European Conference on Machine Learning, 2008, vol. 5211, no. Part 1, pp. 133–145.
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[23]
2008 | Conference Paper | IST-REx-ID: 3706
C. Lampert and M. Blaschko, “Joint kernel support estimation for structured prediction,” presented at the NIPS SISO: NIPS Workshop on “Structured Input - Structured Output,” 2008, pp. 1–4.
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[22]
2008 | Conference Paper | IST-REx-ID: 3694
M. Goldstein, C. Lampert, M. Reif, A. Stahl, and T. Breuel, “Bayes optimal DDoS mitigation by adaptive history-based IP filtering,” presented at the ICN: International Conference on Networking, 2008, pp. 174–179.
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[21]
2008 | Conference Paper | IST-REx-ID: 3714
C. Lampert, M. Blaschko, and T. Hofmann, “Beyond sliding windows: Object localization by efficient subwindow search,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
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[20]
2008 | Conference Paper | IST-REx-ID: 3716
C. Lampert and M. Blaschko, “A multiple kernel learning approach to joint multi-class object detection,” presented at the DAGM: German Association For Pattern Recognition, 2008, vol. 5096, pp. 31–40.
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[19]
2008 | Conference Paper | IST-REx-ID: 3700
C. Lampert, “Partitioning of image datasets using discriminative context information,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
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[18]
2008 | Conference Paper | IST-REx-ID: 3705
M. Blaschko and C. Lampert, “Learning to localize objects with structured output regression,” presented at the ECCV: European Conference on Computer Vision, 2008, vol. 5302, pp. 2–15.
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[17]
2008 | Conference Paper | IST-REx-ID: 3712
M. Blaschko and C. Lampert, “Correlational spectral clustering,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
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[16]
2007 | Conference Paper | IST-REx-ID: 3681
A. Ulges, C. Lampert, D. Keysers, and T. Breuel, “Optimal dominant motion estimation using adaptive search of transformation space,” presented at the DAGM: German Association For Pattern Recognition, 2007, vol. 4713, pp. 204–213.
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[15]
2007 | Conference Paper | IST-REx-ID: 3701
A. Ulges, C. Lampert, D. Keysers, and T. Breuel, “Optimal dominant motion estimation using adaptive search of transformation space,” presented at the DAGM: German Association For Pattern Recognition, 2007, vol. 4713, pp. 204–213.
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[14]
2007 | Report | IST-REx-ID: 3687
M. Blaschko, T. Hofmann, and C. Lampert, Efficient subwindow search for object localization, no. 164. Max-Planck-Institute for Biological Cybernetics, 2007.
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[13]
2006 | Conference Paper | IST-REx-ID: 3679
H. Ali, C. Lampert, and T. Breuel, “Satellite tracks removal in astronomical images,” presented at the CIARP: Iberoamerican Congress in Pattern Recognition, 2006, vol. 4225, pp. 892–901.
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[12]
2006 | Conference Paper | IST-REx-ID: 3693
C. Lampert and O. Wirjadi, “Anisotropic Gaussian filtering using fixed point arithmetic,” presented at the ICIP: IEEE International Conference on Image Processing, 2006, pp. 1565–1568.
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[11]
2006 | Conference Paper | IST-REx-ID: 3683
C. Lampert and T. Breuel, “Objective quality measurement for geometric document image restoration,” presented at the DAS: Document Analysis Systems, 2006.
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[10]
2006 | Journal Article | IST-REx-ID: 3695   OA
C. Lampert and O. Wirjadi, “An optimal non-orthogonal separation of the anisotropic Gaussian convolution filter,” IEEE Transactions on Image Processing (TIP), vol. 15, no. 11, pp. 3501–3513, 2006.
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[9]
2006 | Conference Paper | IST-REx-ID: 3677
A. Ulges, C. Lampert, and D. Keysers, “Spatiogram-based shot distances for video retrieval,” presented at the TRECVID Workshop, 2006, pp. 1–10.
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[8]
2006 | Conference Paper | IST-REx-ID: 3680
C. Lampert, L. Mei, and T. Breuel, “Printing technique classification for document counterfeit detection,” presented at the CIS: Computational Intelligence and Security, 2006, vol. 1, pp. 639–634.
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[7]
2006 | Conference Paper | IST-REx-ID: 3685
C. Lampert, “Machine learning for video compression: Macroblock mode decision,” presented at the ICPR: International Conference on Pattern Recognition, 2006, pp. 936–940.
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[6]
2006 | Conference Paper | IST-REx-ID: 3692
D. Keysers, C. Lampert, and T. Breuel, “Color image dequantization by constrained diffusion,” presented at the SPIE Electronic Imaging, 2006, vol. 6058.
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[5]
2005 | Conference Paper | IST-REx-ID: 3684
C. Lampert, T. Braun, A. Ulges, D. Keysers, and T. Breuel, “Oblivious document capture and real-time retrieval,” presented at the CBDAR: Camera Based Document Analysis and Recognition , 2005, pp. 79–86.
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[4]
2005 | Conference Paper | IST-REx-ID: 3689
A. Ulges, C. Lampert, and T. Breuel, “Document image dewarping using robust estimation of curled text lines,” presented at the ICDAR: International Conference on Document Analysis and Recognition, 2005, vol. 2, pp. 1001–1005.
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[3]
2005 | Journal Article | IST-REx-ID: 3691
C. Lampert, “Boundary regularity of admissible operators,” Publicacions Matemàtiques, vol. 49, no. 1, pp. 179–195, 2005.
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[2]
2004 | Conference Paper | IST-REx-ID: 3688
A. Ulges, C. Lampert, and T. Breuel, “Document capture using stereo vision,” presented at the DocEng: ACM Symposium on Document Engineering, 2004, pp. 198–200.
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[1]
2003 | Thesis | IST-REx-ID: 3678
C. Lampert, The Neumann operator in strictly pseudoconvex domains with weighted Bergman metric , vol. 356. Universität Bonn, Fachbibliothek Mathematik, 2003, pp. 1–165.
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[99]
2019 | Book (Editor) | IST-REx-ID: 7171
K. Kersting, C. Lampert, and C. Rothkopf, Eds., Wie Maschinen lernen. Springer Nature, 2019.
View | Files available | DOI
 
[98]
2019 | Journal Article | IST-REx-ID: 6554   OA
Y. Xian, C. Lampert, B. Schiele, and Z. Akata, “Zero-shot learning - A comprehensive evaluation of the good, the bad and the ugly,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 9, pp. 2251–2265, 2019.
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[97]
2019 | Conference Paper | IST-REx-ID: 6942   OA
P. Ashok, T. Brázdil, K. Chatterjee, J. Křetínský, C. Lampert, and V. Toman, “Strategy representation by decision trees with linear classifiers,” in 16th International Conference on Quantitative Evaluation of Systems, Glasgow, United Kingdom, 2019, vol. 11785, pp. 109–128.
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[96]
2019 | Conference Paper | IST-REx-ID: 6569   OA
P. Bui Thi Mai and C. Lampert, “Towards understanding knowledge distillation,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, United States, 2019, vol. 97, pp. 5142–5151.
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[95]
2019 | Conference Paper | IST-REx-ID: 6590   OA
N. H. Konstantinov and C. Lampert, “Robust learning from untrusted sources,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, USA.
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[94]
2019 | Conference Paper | IST-REx-ID: 6482
R. Sun and C. Lampert, “KS(conf): A light-weight test if a ConvNet operates outside of Its specifications,” presented at the GCPR: Conference on Pattern Recognition, Stuttgart, Germany, 2019, vol. 11269, pp. 244–259.
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[93]
2019 | Journal Article | IST-REx-ID: 6944   OA
R. Sun and C. Lampert, “KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications,” International Journal of Computer Vision, 2019.
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[92]
2018 | Journal Article | IST-REx-ID: 321
T. Darrell, C. Lampert, N. Sebe, Y. Wu, and Y. Yan, “Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, pp. 1029–1031, 2018.
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[91]
2018 | Conference Paper | IST-REx-ID: 6011   OA
I. Kuzborskij and C. Lampert, “Data-dependent stability of stochastic gradient descent,” in Proceedings of the 35 th International Conference on Machine Learning, Stockholm, Sweden, 2018, vol. 80, pp. 2815–2824.
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[90]
2018 | Conference Paper | IST-REx-ID: 6012   OA
S. Sahoo, C. Lampert, and G. S. Martius, “Learning equations for extrapolation and control,” in Proceedings of the 35th International Conference on Machine Learning, Stockholm, Sweden, 2018, vol. 80, pp. 4442–4450.
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[89]
2017 | Conference Paper | IST-REx-ID: 911   OA
A. Royer, A. Kolesnikov, and C. Lampert, “Probabilistic image colorization,” presented at the BMVC: British Machine Vision Conference, London, United Kingdom.
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[88]
2017 | Conference Paper | IST-REx-ID: 1000   OA
A. Kolesnikov and C. Lampert, “PixelCNN models with auxiliary variables for natural image modeling,” presented at the ICML: International Conference on Machine Learning, Sydney, Australia, 2017, vol. 70, pp. 1905–1914.
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[87]
2017 | Conference Paper | IST-REx-ID: 6841   OA
G. S. Martius and C. Lampert, “Extrapolation and learning equations,” in 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings, Toulon, France, 2017.
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[86]
2017 | Conference Paper | IST-REx-ID: 998   OA
S. A. Rebuffi, A. Kolesnikov, G. Sperl, and C. Lampert, “iCaRL: Incremental classifier and representation learning,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 5533–5542.
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[85]
2017 | Conference Paper | IST-REx-ID: 999   OA
A. Pentina and C. Lampert, “Multi-task learning with labeled and unlabeled tasks,” presented at the ICML: International Conference on Machine Learning, Sydney, Australia, 2017, vol. 70, pp. 2807–2816.
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[84]
2017 | Conference Paper | IST-REx-ID: 1108   OA
A. Zimin and C. Lampert, “Learning theory for conditional risk minimization,” presented at the AISTATS: Artificial Intelligence and Statistics, Fort Lauderdale, FL, United States, 2017, vol. 54, pp. 213–222.
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[83]
2017 | Conference Paper | IST-REx-ID: 750
J. Pielorz, M. Prandtstetter, M. Straub, and C. Lampert, “Optimal geospatial volunteer allocation needs realistic distances,” in 2017 IEEE International Conference on Big Data, Boston, MA, United States, 2017, pp. 3760–3763.
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[82]
2016 | Conference Paper | IST-REx-ID: 1369   OA
A. Kolesnikov and C. Lampert, “Seed, expand and constrain: Three principles for weakly-supervised image segmentation,” presented at the ECCV: European Conference on Computer Vision, Amsterdam, The Netherlands, 2016, vol. 9908, pp. 695–711.
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[81]
2016 | Conference Paper | IST-REx-ID: 1707
J. Pielorz and C. Lampert, “Optimal geospatial allocation of volunteers for crisis management,” presented at the ICT-DM: Information and Communication Technologies for Disaster Management, Rennes, France, 2016.
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[80]
2016 | Conference Paper | IST-REx-ID: 1102   OA
A. Kolesnikov and C. Lampert, “Improving weakly-supervised object localization by micro-annotation,” in Proceedings of the British Machine Vision Conference 2016, York, United Kingdom, 2016, vol. 2016–September, p. 92.1-92.12.
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[79]
2015 | Conference Paper | IST-REx-ID: 1857   OA
A. Pentina, V. Sharmanska, and C. Lampert, “Curriculum learning of multiple tasks,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 5492–5500.
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[78]
2015 | Conference Paper | IST-REx-ID: 1858   OA
C. Lampert, “Predicting the future behavior of a time-varying probability distribution,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 942–950.
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[77]
2015 | Conference Paper | IST-REx-ID: 1860   OA
A. Royer and C. Lampert, “Classifier adaptation at prediction time,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 1401–1409.
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[76]
2015 | Conference Paper | IST-REx-ID: 1859   OA
N. Shah, V. Kolmogorov, and C. Lampert, “A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA, 2015, pp. 2737–2745.
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[75]
2015 | Conference Paper | IST-REx-ID: 1425   OA
A. Pentina and C. Lampert, “Lifelong learning with non-i.i.d. tasks,” presented at the NIPS: Neural Information Processing Systems, Montreal, Canada, 2015, vol. 2015, pp. 1540–1548.
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[74]
2014 | Conference Paper | IST-REx-ID: 2171   OA
A. Kolesnikov, M. Guillaumin, V. Ferrari, and C. Lampert, “Closed-form approximate CRF training for scalable image segmentation,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Zurich, Switzerland, 2014, vol. 8691, no. PART 3, pp. 550–565.
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[73]
2014 | Conference Paper | IST-REx-ID: 2033   OA
D. Hernandez Lobato, V. Sharmanska, K. Kersting, C. Lampert, and N. Quadrianto, “Mind the nuisance: Gaussian process classification using privileged noise,” in Advances in Neural Information Processing Systems, Montreal, Canada, 2014, vol. 1, no. January, pp. 837–845.
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[72]
2014 | Conference Paper | IST-REx-ID: 2172
V. Sydorov, M. Sakurada, and C. Lampert, “Deep Fisher Kernels – End to end learning of the Fisher Kernel GMM parameters,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Columbus, USA, 2014, pp. 1402–1409.
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[71]
2014 | Conference Paper | IST-REx-ID: 2160   OA
A. Pentina and C. Lampert, “A PAC-Bayesian bound for Lifelong Learning,” presented at the ICML: International Conference on Machine Learning, Beijing, China, 2014, vol. 32, pp. 991–999.
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[70]
2014 | Conference Paper | IST-REx-ID: 2173   OA
S. Khamis and C. Lampert, “CoConut: Co-classification with output space regularization,” in Proceedings of the British Machine Vision Conference 2014, Nottingham, UK, 2014.
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[69]
2014 | Book Chapter | IST-REx-ID: 1829
K. Muelling, O. Kroemer, C. Lampert, and B. Schölkopf, “Movement templates for learning of hitting and batting,” in Learning Motor Skills, vol. 97, J. Kober and J. Peters, Eds. Springer, 2014, pp. 69–82.
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[68]
2013 | Conference Paper | IST-REx-ID: 2948   OA
T. Tommasi, N. Quadrianto, B. Caputo, and C. Lampert, “Beyond dataset bias: Multi-task unaligned shared knowledge transfer,” vol. 7724. Springer, pp. 1–15, 2013.
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[67]
2013 | Encyclopedia Article | IST-REx-ID: 3321
N. Quadrianto and C. Lampert, “Kernel based learning,” in Encyclopedia of Systems Biology, vol. 3, W. Dubitzky, O. Wolkenhauer, K. Cho, and H. Yokota, Eds. Springer, 2013, pp. 1069–1069.
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[66]
2013 | Conference Paper | IST-REx-ID: 2901   OA
C. Chen, V. Kolmogorov, Z. Yan, D. Metaxas, and C. Lampert, “Computing the M most probable modes of a graphical model,” presented at the AISTATS: Conference on Uncertainty in Artificial Intelligence, Scottsdale, AZ, United States, 2013, vol. 31, pp. 161–169.
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[65]
2013 | Conference Paper | IST-REx-ID: 2293   OA
V. Sharmanska, N. Quadrianto, and C. Lampert, “Learning to rank using privileged information,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013, pp. 825–832.
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[64]
2013 | Journal Article | IST-REx-ID: 2516
C. Lampert, H. Nickisch, and S. Harmeling, “Attribute-based classification for zero-shot learning of object categories,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 3, pp. 453–465, 2013.
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[63]
2013 | Conference Paper | IST-REx-ID: 2294   OA
T. Kazmar, E. Kvon, A. Stark, and C. Lampert, “Drosophila Embryo Stage Annotation using Label Propagation,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013.
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[62]
2012 | Conference Paper | IST-REx-ID: 3124
F. Korc, V. Kolmogorov, and C. Lampert, “Approximating marginals using discrete energy minimization,” presented at the ICML: International Conference on Machine Learning, Edinburgh, Scotland, 2012.
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[61]
2012 | Technical Report | IST-REx-ID: 5396   OA
F. Korc, V. Kolmogorov, and C. Lampert, Approximating marginals using discrete energy minimization. IST Austria, 2012.
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[60]
2012 | Conference Paper | IST-REx-ID: 3125
V. Sharmanska, N. Quadrianto, and C. Lampert, “Augmented attribute representations,” presented at the ECCV: European Conference on Computer Vision, Florence, Italy, 2012, vol. 7576, no. PART 5, pp. 242–255.
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[59]
2012 | Conference Paper | IST-REx-ID: 2825
C. Lampert, “Dynamic pruning of factor graphs for maximum marginal prediction,” presented at the NIPS: Neural Information Processing Systems, Lake Tahoe, NV, United States, 2012, vol. 1, pp. 82–90.
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[58]
2012 | Conference Paper | IST-REx-ID: 3126
A. Müller, S. Nowozin, and C. Lampert, “Information theoretic clustering using minimal spanning trees,” presented at the DAGM: German Association For Pattern Recognition, Graz, Austria, 2012, vol. 7476, pp. 205–215.
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[57]
2012 | Journal Article | IST-REx-ID: 3164
M. Blaschko and C. Lampert, “Guest editorial: Special issue on structured prediction and inference,” International Journal of Computer Vision, vol. 99, no. 3, pp. 257–258, 2012.
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[56]
2012 | Conference Paper | IST-REx-ID: 2915
O. Kroemer, C. Lampert, and J. Peters, “Multi-modal learning for dynamic tactile sensing,” 2012.
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[55]
2012 | Conference Paper | IST-REx-ID: 3127   OA
N. Quadrianto, C. Lampert, and C. Chen, “The most persistent soft-clique in a set of sampled graphs,” in Proceedings of the 29th International Conference on Machine Learning, Edinburgh, United Kingdom, 2012, pp. 211–218.
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[54]
2012 | Journal Article | IST-REx-ID: 3248   OA
C. Lampert and J. Peters, “Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components,” Journal of Real-Time Image Processing, vol. 7, no. 1, pp. 31–41, 2012.
View | Files available | DOI
 
[53]
2011 | Conference Paper | IST-REx-ID: 3319
N. Quadrianto and C. Lampert, “Learning multi-view neighborhood preserving projections,” presented at the ICML: International Conference on Machine Learning, Bellevue, USA, 2011, pp. 425–432.
View
 
[52]
2011 | Conference Paper | IST-REx-ID: 3163
C. Lampert, “Maximum margin multi-label structured prediction,” presented at the NIPS: Neural Information Processing Systems, Granada, Spain, 2011.
View | Files available
 
[51]
2011 | Conference Poster | IST-REx-ID: 3322
C. Lampert, Maximum margin multi label structured prediction. Neural Information Processing Systems, 2011.
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[50]
2011 | Journal Article | IST-REx-ID: 3389
M. Blaschko, J. Shelton, A. Bartels, C. Lampert, and A. Gretton, “Semi supervised kernel canonical correlation analysis with application to human fMRI,” Pattern Recognition Letters, vol. 32, no. 11, pp. 1572–1583, 2011.
View | DOI
 
[49]
2011 | Technical Report | IST-REx-ID: 5386   OA
C. Chen, D. Freedman, and C. Lampert, Enforcing topological constraints in random field image segmentation. IST Austria, 2011.
View | Files available | DOI
 
[48]
2011 | Conference Paper | IST-REx-ID: 3336
C. Chen, D. Freedman, and C. Lampert, “Enforcing topological constraints in random field image segmentation,” in CVPR: Computer Vision and Pattern Recognition, Colorado Springs, CO, USA, 2011, pp. 2089–2096.
View | Files available | DOI
 
[47]
2011 | Journal Article | IST-REx-ID: 3320
S. Nowozin and C. Lampert, “Structured learning and prediction in computer vision,” Foundations and Trends in Computer Graphics and Vision, vol. 6, no. 3–4, pp. 185–365, 2011.
View | DOI
 
[46]
2011 | Journal Article | IST-REx-ID: 3382
O. Kroemer, C. Lampert, and J. Peters, “Learning dynamic tactile sensing with robust vision based training,” IEEE Transactions on Robotics, vol. 27, no. 3, pp. 545–557, 2011.
View | DOI
 
[45]
2011 | Conference Paper | IST-REx-ID: 3337
Z. Wang, C. Lampert, K. Mülling, B. Schölkopf, and J. Peters, “Learning anticipation policies for robot table tennis,” presented at the IROS: RSJ International Conference on Intelligent Robots and Systems, San Francisco, USA, 2011, pp. 332–337.
View | DOI
 
[44]
2010 | Conference Paper | IST-REx-ID: 3794
C. Lampert and O. Krömer, “Weakly-paired maximum covariance analysis for multimodal dimensionality reduction and transfer learning,” presented at the ECCV: European Conference on Computer Vision, Heraklion, Crete, Greece, 2010, vol. 6312, pp. 566–579.
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[43]
2010 | Journal Article | IST-REx-ID: 3686
S. Nowozin and C. Lampert, “Global interactions in random field models: A potential function ensuring connectedness,” SIAM Journal on Imaging Sciences, vol. 3, no. 4 (Special Section on Optimization in Imaging Sciences), pp. 1048–1074, 2010.
View | DOI
 
[42]
2010 | Conference Paper | IST-REx-ID: 3713
C. Lampert, “An efficient divide-and-conquer cascade for nonlinear object detection,” presented at the CVPR: Computer Vision and Pattern Recognition, 2010, pp. 1022–1029.
View | DOI
 
[41]
2010 | Conference Paper | IST-REx-ID: 3682
K. Tang, M. Tappen, R. Sukthankar, and C. Lampert, “Optimizing one-shot recognition with micro-set learning,” presented at the CVPR: Computer Vision and Pattern Recognition, 2010, pp. 3027–3034.
View | DOI
 
[40]
2010 | Conference Paper | IST-REx-ID: 3702
J. Kober, K. Mülling, O. Krömer, C. Lampert, B. Schölkopf, and J. Peters, “Movement templates for learning of hitting and batting,” presented at the ICRA: International Conference on Robotics and Automation, 2010, pp. 853–858.
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[39]
2010 | Conference Paper | IST-REx-ID: 3676
J. Wanke, A. Ulges, C. Lampert, and T. Breuel, “Topic models for semantic video compression,” presented at the MIR: Multimedia Information Retrieval, 2010, pp. 275–284.
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[38]
2010 | Conference Paper | IST-REx-ID: 3793
S. Nowozin, P. Gehler, and C. Lampert, “On parameter learning in CRF-based approaches to object class image segmentation,” presented at the ECCV: European Conference on Computer Vision, Heraklion, Crete, Greece, 2010, vol. 6316, pp. 98–111.
View | DOI
 
[37]
2010 | Journal Article | IST-REx-ID: 3697
T. Tuytelaars, C. Lampert, M. Blaschko, and W. Buntine, “Unsupervised object discovery: A comparison,” International Journal of Computer Vision, vol. 88, no. 2, pp. 284–302, 2010.
View | DOI
 
[36]
2009 | Conference Poster | IST-REx-ID: 3699
M. Blaschko, C. Lampert, and A. Bartels, Semi-supervised analysis of human fMRI data. Berlin Institute of Technology, 2009.
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[35]
2009 | Book | IST-REx-ID: 3707
C. Lampert, Kernel methods in computer vision, vol. 4. now, 2009, pp. 193–285.
View | DOI
 
[34]
2009 | Conference Paper | IST-REx-ID: 3690
P. Dhillon, S. Nowozin, and C. Lampert, “Combining appearance and motion for human action classification in videos,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, no. 174, pp. 22–29.
View | DOI
 
[33]
2009 | Conference Paper | IST-REx-ID: 3703
M. Blaschko and C. Lampert, “Object localization with global and local context kernels,” presented at the BMVC: British Machine Vision Conference, 2009, pp. 1–11.
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[32]
2009 | Conference Paper | IST-REx-ID: 3708
S. Nowozin and C. Lampert, “Global connectivity potentials for random field models,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 818–825.
View | DOI
 
[31]
2009 | Journal Article | IST-REx-ID: 3710
C. Lampert, M. Blaschko, and T. Hofmann, “Efficient subwindow search: A branch and bound framework for object localization,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 12, pp. 2129–2142, 2009.
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[30]
2009 | Conference Paper | IST-REx-ID: 3715
C. Lampert and J. Peters, “Active structured learning for high-speed object detection,” presented at the DAGM: German Association For Pattern Recognition, 2009, vol. 5748, pp. 221–231.
View | DOI
 
[29]
2009 | Journal Article | IST-REx-ID: 3696
C. Lampert and M. Blaschko, “Structured prediction by joint kernel support estimation,” Machine Learning, vol. 77, no. 2–3, pp. 249–269, 2009.
View | DOI
 
[28]
2009 | Conference Paper | IST-REx-ID: 3704
C. Lampert, H. Nickisch, and S. Harmeling, “Learning to detect unseen object classes by between-class attribute transfer,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 951–958.
View | DOI
 
[27]
2009 | Conference Paper | IST-REx-ID: 3709
C. Lampert, “Detecting objects in large image collections and videos by efficient subimage retrieval,” presented at the ICCV: International Conference on Computer Vision, 2009, pp. 987–994.
View | DOI
 
[26]
2009 | Conference Paper | IST-REx-ID: 3711
P. Dhillon, S. Nowozin, and C. Lampert, “Combining appearance and motion for human action classification in videos,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 22–29.
View | DOI | Download (ext.)
 
[25]
2009 | Conference Poster | IST-REx-ID: 3717
C. Lampert and J. Peters, A high-speed object tracker from off-the-shelf components. IEEE, 2009.
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[24]
2008 | Conference Paper | IST-REx-ID: 3698
M. Blaschko, C. Lampert, and A. Gretton, “Semi-supervised Laplacian regularization of kernel canonical correlation analysis,” presented at the ECML: European Conference on Machine Learning, 2008, vol. 5211, no. Part 1, pp. 133–145.
View | DOI
 
[23]
2008 | Conference Paper | IST-REx-ID: 3706
C. Lampert and M. Blaschko, “Joint kernel support estimation for structured prediction,” presented at the NIPS SISO: NIPS Workshop on “Structured Input - Structured Output,” 2008, pp. 1–4.
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[22]
2008 | Conference Paper | IST-REx-ID: 3694
M. Goldstein, C. Lampert, M. Reif, A. Stahl, and T. Breuel, “Bayes optimal DDoS mitigation by adaptive history-based IP filtering,” presented at the ICN: International Conference on Networking, 2008, pp. 174–179.
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[21]
2008 | Conference Paper | IST-REx-ID: 3714
C. Lampert, M. Blaschko, and T. Hofmann, “Beyond sliding windows: Object localization by efficient subwindow search,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
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[20]
2008 | Conference Paper | IST-REx-ID: 3716
C. Lampert and M. Blaschko, “A multiple kernel learning approach to joint multi-class object detection,” presented at the DAGM: German Association For Pattern Recognition, 2008, vol. 5096, pp. 31–40.
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[19]
2008 | Conference Paper | IST-REx-ID: 3700
C. Lampert, “Partitioning of image datasets using discriminative context information,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
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[18]
2008 | Conference Paper | IST-REx-ID: 3705
M. Blaschko and C. Lampert, “Learning to localize objects with structured output regression,” presented at the ECCV: European Conference on Computer Vision, 2008, vol. 5302, pp. 2–15.
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[17]
2008 | Conference Paper | IST-REx-ID: 3712
M. Blaschko and C. Lampert, “Correlational spectral clustering,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
View | DOI
 
[16]
2007 | Conference Paper | IST-REx-ID: 3681
A. Ulges, C. Lampert, D. Keysers, and T. Breuel, “Optimal dominant motion estimation using adaptive search of transformation space,” presented at the DAGM: German Association For Pattern Recognition, 2007, vol. 4713, pp. 204–213.
View | DOI
 
[15]
2007 | Conference Paper | IST-REx-ID: 3701
A. Ulges, C. Lampert, D. Keysers, and T. Breuel, “Optimal dominant motion estimation using adaptive search of transformation space,” presented at the DAGM: German Association For Pattern Recognition, 2007, vol. 4713, pp. 204–213.
View | DOI
 
[14]
2007 | Report | IST-REx-ID: 3687
M. Blaschko, T. Hofmann, and C. Lampert, Efficient subwindow search for object localization, no. 164. Max-Planck-Institute for Biological Cybernetics, 2007.
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[13]
2006 | Conference Paper | IST-REx-ID: 3679
H. Ali, C. Lampert, and T. Breuel, “Satellite tracks removal in astronomical images,” presented at the CIARP: Iberoamerican Congress in Pattern Recognition, 2006, vol. 4225, pp. 892–901.
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[12]
2006 | Conference Paper | IST-REx-ID: 3693
C. Lampert and O. Wirjadi, “Anisotropic Gaussian filtering using fixed point arithmetic,” presented at the ICIP: IEEE International Conference on Image Processing, 2006, pp. 1565–1568.
View | DOI
 
[11]
2006 | Conference Paper | IST-REx-ID: 3683
C. Lampert and T. Breuel, “Objective quality measurement for geometric document image restoration,” presented at the DAS: Document Analysis Systems, 2006.
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[10]
2006 | Journal Article | IST-REx-ID: 3695   OA
C. Lampert and O. Wirjadi, “An optimal non-orthogonal separation of the anisotropic Gaussian convolution filter,” IEEE Transactions on Image Processing (TIP), vol. 15, no. 11, pp. 3501–3513, 2006.
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[9]
2006 | Conference Paper | IST-REx-ID: 3677
A. Ulges, C. Lampert, and D. Keysers, “Spatiogram-based shot distances for video retrieval,” presented at the TRECVID Workshop, 2006, pp. 1–10.
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[8]
2006 | Conference Paper | IST-REx-ID: 3680
C. Lampert, L. Mei, and T. Breuel, “Printing technique classification for document counterfeit detection,” presented at the CIS: Computational Intelligence and Security, 2006, vol. 1, pp. 639–634.
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[7]
2006 | Conference Paper | IST-REx-ID: 3685
C. Lampert, “Machine learning for video compression: Macroblock mode decision,” presented at the ICPR: International Conference on Pattern Recognition, 2006, pp. 936–940.
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[6]
2006 | Conference Paper | IST-REx-ID: 3692
D. Keysers, C. Lampert, and T. Breuel, “Color image dequantization by constrained diffusion,” presented at the SPIE Electronic Imaging, 2006, vol. 6058.
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[5]
2005 | Conference Paper | IST-REx-ID: 3684
C. Lampert, T. Braun, A. Ulges, D. Keysers, and T. Breuel, “Oblivious document capture and real-time retrieval,” presented at the CBDAR: Camera Based Document Analysis and Recognition , 2005, pp. 79–86.
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[4]
2005 | Conference Paper | IST-REx-ID: 3689
A. Ulges, C. Lampert, and T. Breuel, “Document image dewarping using robust estimation of curled text lines,” presented at the ICDAR: International Conference on Document Analysis and Recognition, 2005, vol. 2, pp. 1001–1005.
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[3]
2005 | Journal Article | IST-REx-ID: 3691
C. Lampert, “Boundary regularity of admissible operators,” Publicacions Matemàtiques, vol. 49, no. 1, pp. 179–195, 2005.
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[2]
2004 | Conference Paper | IST-REx-ID: 3688
A. Ulges, C. Lampert, and T. Breuel, “Document capture using stereo vision,” presented at the DocEng: ACM Symposium on Document Engineering, 2004, pp. 198–200.
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[1]
2003 | Thesis | IST-REx-ID: 3678
C. Lampert, The Neumann operator in strictly pseudoconvex domains with weighted Bergman metric , vol. 356. Universität Bonn, Fachbibliothek Mathematik, 2003, pp. 1–165.
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