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136 Publications


2014 | Published | 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.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | arXiv
 

2014 | Published | 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.
View | DOI | WoS
 

2014 | Published | 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.
[Published Version] View | Files available
 

2014 | Published | Journal Article | IST-REx-ID: 2180 | OA
A. Bellet, A. Habrard, E. Morvant, and M. Sebban, “Learning a priori constrained weighted majority votes,” Machine Learning, vol. 97, no. 1–2. Springer, pp. 129–154, 2014.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 

2014 | Published | Conference Paper | IST-REx-ID: 2189 | OA
E. Morvant, “Adaptation de domaine de vote de majorité par auto-étiquetage non itératif,” presented at the CAP: Conférence Francophone sur l’Apprentissage Automatique (Machine Learning French Conference), Saint-Etienne, France, 2014, vol. 1, pp. 49–58.
[Preprint] View | Download Preprint (ext.)
 

2014 | Published | 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.
[Submitted Version] View | Download Submitted Version (ext.)
 

2014 | Published | Conference Paper | IST-REx-ID: 2051 | OA
M. Marchand, S. Hongyu, E. Morvant, J. Rousu, and J. Shawe Taylor, “Multilabel structured output learning with random spanning trees of max-margin Markov networks,” in Advances in Neural Information Processing Systems, Montreal, Canada, 2014, vol. 27.
[Published Version] View | Download Published Version (ext.)
 

2014 | Published | Conference Paper | IST-REx-ID: 2057 | OA
E. Morvant, A. Habrard, and S. Ayache, “Majority vote of diverse classifiers for late fusion,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Joensuu, Finland, 2014, vol. 8621, pp. 153–162.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2014 | Published | 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.
View | DOI
 

2013 | Published | 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.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 

2013 | Published | 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.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 

2013 | Published | 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. IEEE, pp. 453–465, 2013.
View | DOI | WoS
 

2013 | Published | Conference Paper | IST-REx-ID: 2520 | OA
N. Quadrianto, V. Sharmanska, D. Knowles, and Z. Ghahramani, “The supervised IBP: Neighbourhood preserving infinite latent feature models,” in Proceedings of the 29th conference uncertainty in Artificial Intelligence, Bellevue, WA, United States, 2013, pp. 527–536.
[Submitted Version] View | Files available
 

2013 | Published | 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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2013 | Published | 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.
[Submitted Version] View | Files available | DOI
 

2013 | Published | 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.
View | DOI
 

2012 | Published | 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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2012 | Published | 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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2012 | Published | Technical Report | IST-REx-ID: 5396 | OA
F. Korc, V. Kolmogorov, and C. Lampert, Approximating marginals using discrete energy minimization. IST Austria, 2012.
[Published Version] View | Files available | DOI
 

earlier version | 2012 | Published | Conference Paper | IST-REx-ID: 3124 | OA
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.
[Submitted Version] View | Files available
 

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