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75 Publications

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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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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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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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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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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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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2018 | Conference Paper | IST-REx-ID: 6589   OA
D.-A. Alistarh, T. Hoefler, M. Johansson, N. H. Konstantinov, S. Khirirat, and C. Renggli, “The convergence of sparsified gradient methods,” in Advances in Neural Information Processing Systems 31, Montreal, Canada, 2018, vol. Volume 2018, pp. 5973–5983.
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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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2018 | 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, pp. 1–1, 2018.
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2018 | Thesis | IST-REx-ID: 68   OA
A. Zimin, Learning from dependent data. IST Austria, 2018.
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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.
View | Files available | Download (ext.) | arXiv
 
2018 | Journal Article | IST-REx-ID: 563   OA
H. Ringbauer, A. Kolesnikov, D. Field, and N. H. Barton, “Estimating barriers to gene flow from distorted isolation-by-distance patterns,” Genetics, vol. 208, no. 3, pp. 1231–1245, 2018.
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2018 | Research Data | IST-REx-ID: 5584
S. Deny, O. Marre, V. Botella-Soler, G. S. Martius, and G. Tkacik, Nonlinear decoding of a complex movie from the mammalian retina. IST Austria, 2018.
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2018 | Thesis | IST-REx-ID: 197   OA
A. Kolesnikov, Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images. IST Austria, 2018.
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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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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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2017 | Conference Paper | IST-REx-ID: 652
R. Der and G. S. Martius, “Dynamical self consistency leads to behavioral development and emergent social interactions in robots,” presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France, 2017.
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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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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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2017 | Journal Article | IST-REx-ID: 658   OA
R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal robots,” Frontiers in Neurorobotics, vol. 11, no. MAR, 2017.
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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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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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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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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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2016 | Conference Paper | IST-REx-ID: 1098   OA
A. Pentina and R. Urner, “Lifelong learning with weighted majority votes,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain, 2016, vol. 29, pp. 3619–3627.
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2016 | Conference Paper | IST-REx-ID: 1214
G. S. Martius, R. Hostettler, A. Knoll, and R. Der, “Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm,” presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea, 2016, vol. 2016–November.
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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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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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2016 | Thesis | IST-REx-ID: 1126   OA
A. Pentina, Theoretical foundations of multi-task lifelong learning. IST Austria, 2016.
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2015 | Journal Article | IST-REx-ID: 1655   OA
G. S. Martius and E. Olbrich, “Quantifying emergent behavior of autonomous robots,” Entropy, vol. 17, no. 10, pp. 7266–7297, 2015.
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2015 | Conference Paper | IST-REx-ID: 1706   OA
A. Pentina and S. Ben David, “Multi-task and lifelong learning of kernels,” presented at the ALT: Algorithmic Learning Theory, Banff, AB, Canada, 2015, vol. 9355, pp. 194–208.
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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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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.
View | DOI | Download (ext.) | arXiv
 
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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2015 | Journal Article | IST-REx-ID: 1570   OA
R. Der and G. S. Martius, “Novel plasticity rule can explain the development of sensorimotor intelligence,” PNAS, vol. 112, no. 45, pp. E6224–E6232, 2015.
View | DOI | Download (ext.) | PubMed | Europe PMC
 
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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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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2015 | Thesis | IST-REx-ID: 1401
V. Sharmanska, Learning with attributes for object recognition: Parametric and non-parametrics views. IST Austria, 2015.
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2015 | Journal Article | IST-REx-ID: 1533
W. Xia, C. Domokos, J. Xiong, L. Cheong, and S. Yan, “Segmentation over detection via optimal sparse reconstructions,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 25, no. 8, pp. 1295–1308, 2015.
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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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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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2014 | 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.
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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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2014 | 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.
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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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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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2014 | 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, pp. 129–154, 2014.
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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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2013 | 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.
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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.
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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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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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2011 | Conference Poster | IST-REx-ID: 3322
C. Lampert, Maximum margin multi label structured prediction. Neural Information Processing Systems, 2011.
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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.
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2011 | Technical Report | IST-REx-ID: 5386
C. Chen, D. Freedman, and C. Lampert, Enforcing topological constraints in random field image segmentation. IST Austria, 2011.
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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.
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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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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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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.
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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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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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