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Jonathan Scott

Egor Zverev

Peter Sukenik

Bernd Prach

Christoph Lampert

Hossein Zakerinia

Nikita Kalinin

Mary Phuong

Daniel Pucher

Csaba Domokos

Paul Henderson

Alexandra Krumes

Nikola Konstantinov

Alexander Zimin

Amélie Royer

Emilie Morvant

Anastasia Pentina

Filip Korc

Georg Martius

Johannes Dostal

Volhejn, Vaclav

Alexander Kolesnikov

Viktoriia Sharmanska



114 Publications

2018 | Research Data | IST-REx-ID: 5584 | OA
Deny, S., Marre, O., Botella-Soler, V., Martius, G. S., & Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:98
[Published Version] View | Files available | DOI
 
2017 | Conference Paper | IST-REx-ID: 652
Der, R., & Martius, G. S. (2017). 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: IEEE. https://doi.org/10.1109/DEVLRN.2016.7846789
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2017 | Journal Article | IST-REx-ID: 658 | OA
Der, R., & Martius, G. S. (2017). Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. Frontiers Research Foundation. https://doi.org/10.3389/fnbot.2017.00008
[Published Version] View | Files available | DOI
 
2017 | Conference Paper | IST-REx-ID: 6841 | OA
Martius, G. S., & Lampert, C. (2017). Extrapolation and learning equations. In 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings. Toulon, France: International Conference on Learning Representations.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2017 | Conference Paper | IST-REx-ID: 750
Pielorz, J., Prandtstetter, M., Straub, M., & Lampert, C. (2017). Optimal geospatial volunteer allocation needs realistic distances. In 2017 IEEE International Conference on Big Data (pp. 3760–3763). Boston, MA, United States: IEEE. https://doi.org/10.1109/BigData.2017.8258375
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2017 | Conference Paper | IST-REx-ID: 1000 | OA
Kolesnikov, A., & Lampert, C. (2017). PixelCNN models with auxiliary variables for natural image modeling. In 34th International Conference on Machine Learning (Vol. 70, pp. 1905–1914). Sydney, Australia: JMLR.
[Submitted Version] View | Download Submitted Version (ext.) | WoS | arXiv
 
2017 | Conference Paper | IST-REx-ID: 998 | OA
Rebuffi, S. A., Kolesnikov, A., Sperl, G., & Lampert, C. (2017). iCaRL: Incremental classifier and representation learning (Vol. 2017, pp. 5533–5542). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.587
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
2017 | Conference Paper | IST-REx-ID: 911 | OA
Royer, A., Kolesnikov, A., & Lampert, C. (2017). Probabilistic image colorization (p. 85.1-85.12). Presented at the BMVC: British Machine Vision Conference, London, United Kingdom: BMVA Press. https://doi.org/10.5244/c.31.85
[Published Version] View | Files available | DOI | arXiv
 
2017 | Conference Paper | IST-REx-ID: 1108 | OA
Zimin, A., & Lampert, C. (2017). Learning theory for conditional risk minimization (Vol. 54, pp. 213–222). Presented at the AISTATS: Artificial Intelligence and Statistics, Fort Lauderdale, FL, United States: ML Research Press.
[Submitted Version] View | Download Submitted Version (ext.) | WoS
 
2017 | Conference Paper | IST-REx-ID: 999 | OA
Pentina, A., & Lampert, C. (2017). Multi-task learning with labeled and unlabeled tasks (Vol. 70, pp. 2807–2816). Presented at the ICML: International Conference on Machine Learning, Sydney, Australia: ML Research Press.
[Submitted Version] View | Download Submitted Version (ext.) | WoS
 
2016 | Conference Paper | IST-REx-ID: 1098 | OA
Pentina, A., & Urner, R. (2016). Lifelong learning with weighted majority votes (Vol. 29, pp. 3619–3627). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain: Neural Information Processing Systems.
[Published Version] View | Files available
 
2016 | Conference Paper | IST-REx-ID: 1102 | OA
Kolesnikov, A., & Lampert, C. (2016). Improving weakly-supervised object localization by micro-annotation. In Proceedings of the British Machine Vision Conference 2016 (Vol. 2016–September, p. 92.1-92.12). York, United Kingdom: BMVA Press. https://doi.org/10.5244/C.30.92
[Published Version] View | DOI | Download Published Version (ext.)
 
2016 | Conference Paper | IST-REx-ID: 1214
Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm (Vol. 2016–November). Presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea: IEEE. https://doi.org/10.1109/IROS.2016.7759138
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2016 | Conference Paper | IST-REx-ID: 1369 | OA
Kolesnikov, A., & Lampert, C. (2016). Seed, expand and constrain: Three principles for weakly-supervised image segmentation (Vol. 9908, pp. 695–711). Presented at the ECCV: European Conference on Computer Vision, Amsterdam, The Netherlands: Springer. https://doi.org/10.1007/978-3-319-46493-0_42
[Preprint] View | DOI | Download Preprint (ext.)
 
2016 | Conference Paper | IST-REx-ID: 1707
Pielorz, J., & Lampert, C. (2016). Optimal geospatial allocation of volunteers for crisis management. Presented at the ICT-DM: Information and Communication Technologies for Disaster Management, Rennes, France: IEEE. https://doi.org/10.1109/ICT-DM.2015.7402041
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2016 | Conference Paper | IST-REx-ID: 8094 | OA
Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Self-organized control of an tendon driven arm by differential extrinsic plasticity. In Proceedings of the Artificial Life Conference 2016 (Vol. 28, pp. 142–143). Cancun, Mexico: MIT Press. https://doi.org/10.7551/978-0-262-33936-0-ch029
[Published Version] View | Files available | DOI
 
2016 | Thesis | IST-REx-ID: 1126 | OA
Pentina, A. (2016). Theoretical foundations of multi-task lifelong learning. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:TH_776
[Published Version] View | Files available | DOI
 
2015 | Conference Paper | IST-REx-ID: 1425 | OA
Pentina, A., & Lampert, C. (2015). Lifelong learning with non-i.i.d. tasks (Vol. 2015, pp. 1540–1548). Presented at the NIPS: Neural Information Processing Systems, Montreal, Canada: Neural Information Processing Systems.
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2015 | Journal Article | IST-REx-ID: 1533
Xia, W., Domokos, C., Xiong, J., Cheong, L., & Yan, S. (2015). Segmentation over detection via optimal sparse reconstructions. IEEE Transactions on Circuits and Systems for Video Technology. IEEE. https://doi.org/10.1109/TCSVT.2014.2379972
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2015 | Journal Article | IST-REx-ID: 1570 | OA
Der, R., & Martius, G. S. (2015). Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1508400112
[Submitted Version] View | DOI | Download Submitted Version (ext.) | PubMed | Europe PMC
 
2015 | Conference Paper | IST-REx-ID: 1706 | OA
Pentina, A., & Ben David, S. (2015). Multi-task and lifelong learning of kernels (Vol. 9355, pp. 194–208). Presented at the ALT: Algorithmic Learning Theory, Banff, AB, Canada: Springer. https://doi.org/10.1007/978-3-319-24486-0_13
[Preprint] View | DOI | Download Preprint (ext.)
 
2015 | Conference Paper | IST-REx-ID: 1859 | OA
Shah, N., Kolmogorov, V., & Lampert, C. (2015). A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle (pp. 2737–2745). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA: IEEE. https://doi.org/10.1109/CVPR.2015.7298890
[Preprint] View | DOI | Download Preprint (ext.)
 
2015 | Conference Paper | IST-REx-ID: 1860 | OA
Royer, A., & Lampert, C. (2015). Classifier adaptation at prediction time (pp. 1401–1409). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States: IEEE. https://doi.org/10.1109/CVPR.2015.7298746
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
2015 | Conference Paper | IST-REx-ID: 1858 | OA
Lampert, C. (2015). Predicting the future behavior of a time-varying probability distribution (pp. 942–950). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States: IEEE. https://doi.org/10.1109/CVPR.2015.7298696
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2015 | Conference Paper | IST-REx-ID: 1857 | OA
Pentina, A., Sharmanska, V., & Lampert, C. (2015). Curriculum learning of multiple tasks (pp. 5492–5500). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States: IEEE. https://doi.org/10.1109/CVPR.2015.7299188
[Preprint] View | DOI | Download Preprint (ext.)
 
2015 | Conference Paper | IST-REx-ID: 12881 | OA
Martius, G. S., & Olbrich, E. (2015). Quantifying self-organizing behavior of autonomous robots. In Proceedings of the 13th European Conference on Artificial Life (p. 78). York, United Kingdom: MIT Press. https://doi.org/10.7551/978-0-262-33027-5-ch018
[Published Version] View | Files available | DOI
 
2015 | Thesis | IST-REx-ID: 1401 | OA
Sharmanska, V. (2015). Learning with attributes for object recognition: Parametric and non-parametrics views. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:1401
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2015 | Journal Article | IST-REx-ID: 1655 | OA
Martius, G. S., & Olbrich, E. (2015). Quantifying emergent behavior of autonomous robots. Entropy. MDPI. https://doi.org/10.3390/e17107266
[Published Version] View | Files available | DOI
 
2014 | Book Chapter | IST-REx-ID: 1829
Muelling, K., Kroemer, O., Lampert, C., & Schölkopf, B. (2014). Movement templates for learning of hitting and batting. In J. Kober & J. Peters (Eds.), Learning Motor Skills (Vol. 97, pp. 69–82). Springer. https://doi.org/10.1007/978-3-319-03194-1_3
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2014 | Conference Paper | IST-REx-ID: 2033 | OA
Hernandez Lobato, D., Sharmanska, V., Kersting, K., Lampert, C., & Quadrianto, N. (2014). Mind the nuisance: Gaussian process classification using privileged noise. In Advances in Neural Information Processing Systems (Vol. 1, pp. 837–845). Montreal, Canada: Neural Information Processing Systems.
[Submitted Version] View | Download Submitted Version (ext.)
 
2014 | Conference Paper | IST-REx-ID: 2057 | OA
Morvant, E., Habrard, A., & Ayache, S. (2014). 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) (Vol. 8621, pp. 153–162). Joensuu, Finland: Springer. https://doi.org/10.1007/978-3-662-44415-3_16
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2014 | Conference Paper | IST-REx-ID: 2171 | OA
Kolesnikov, A., Guillaumin, M., Ferrari, V., & Lampert, C. (2014). Closed-form approximate CRF training for scalable image segmentation. In D. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8691, pp. 550–565). Zurich, Switzerland: Springer. https://doi.org/10.1007/978-3-319-10578-9_36
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
2014 | Conference Paper | IST-REx-ID: 2173 | OA
Khamis, S., & Lampert, C. (2014). CoConut: Co-classification with output space regularization. In Proceedings of the British Machine Vision Conference 2014. Nottingham, UK: BMVA Press.
[Published Version] View | Files available
 
2014 | Conference Paper | IST-REx-ID: 2172
Sydorov, V., Sakurada, M., & Lampert, C. (2014). 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 (pp. 1402–1409). Columbus, USA: IEEE. https://doi.org/10.1109/CVPR.2014.182
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2014 | Journal Article | IST-REx-ID: 2180 | OA
Bellet, A., Habrard, A., Morvant, E., & Sebban, M. (2014). Learning a priori constrained weighted majority votes. Machine Learning. Springer. https://doi.org/10.1007/s10994-014-5462-z
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
2014 | Conference Paper | IST-REx-ID: 2189 | OA
Morvant, E. (2014). Adaptation de domaine de vote de majorité par auto-étiquetage non itératif (Vol. 1, pp. 49–58). Presented at the CAP: Conférence Francophone sur l’Apprentissage Automatique (Machine Learning French Conference), Saint-Etienne, France: Elsevier.
[Preprint] View | Download Preprint (ext.)
 
2014 | Conference Paper | IST-REx-ID: 2160 | OA
Pentina, A., & Lampert, C. (2014). A PAC-Bayesian bound for Lifelong Learning (Vol. 32, pp. 991–999). Presented at the ICML: International Conference on Machine Learning, Beijing, China: ML Research Press.
[Submitted Version] View | Download Submitted Version (ext.)
 
2013 | Conference Paper | IST-REx-ID: 2294 | OA
Kazmar, T., Kvon, E., Stark, A., & Lampert, C. (2013). Drosophila Embryo Stage Annotation using Label Propagation. Presented at the ICCV: International Conference on Computer Vision, Sydney, Australia: IEEE. https://doi.org/10.1109/ICCV.2013.139
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
2013 | Conference Paper | IST-REx-ID: 2293 | OA
Sharmanska, V., Quadrianto, N., & Lampert, C. (2013). Learning to rank using privileged information (pp. 825–832). Presented at the ICCV: International Conference on Computer Vision, Sydney, Australia: IEEE. https://doi.org/10.1109/ICCV.2013.107
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
2013 | Journal Article | IST-REx-ID: 2516
Lampert, C., Nickisch, H., & Harmeling, S. (2013). Attribute-based classification for zero-shot learning of object categories. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2013.140
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2013 | Conference Paper | IST-REx-ID: 2520 | OA
Quadrianto, N., Sharmanska, V., Knowles, D., & Ghahramani, Z. (2013). The supervised IBP: Neighbourhood preserving infinite latent feature models. In Proceedings of the 29th conference uncertainty in Artificial Intelligence (pp. 527–536). Bellevue, WA, United States: AUAI Press.
[Submitted Version] View | Files available
 
2013 | Conference Paper | IST-REx-ID: 2901 | OA
Chen, C., Kolmogorov, V., Yan, Z., Metaxas, D., & Lampert, C. (2013). Computing the M most probable modes of a graphical model (Vol. 31, pp. 161–169). Presented at the AISTATS: Conference on Uncertainty in Artificial Intelligence, Scottsdale, AZ, United States: JMLR.
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2013 | Conference Paper | IST-REx-ID: 2948 | OA
Tommasi, T., Quadrianto, N., Caputo, B., & Lampert, C. (2013). Beyond dataset bias: Multi-task unaligned shared knowledge transfer. Presented at the ACCV: Asian Conference on Computer Vision, Daejeon, Korea: Springer. https://doi.org/10.1007/978-3-642-37331-2_1
[Submitted Version] View | Files available | DOI
 
2013 | Encyclopedia Article | IST-REx-ID: 3321
Quadrianto, N., & Lampert, C. (2013). Kernel based learning. In W. Dubitzky, O. Wolkenhauer, K. Cho, & H. Yokota (Eds.), Encyclopedia of Systems Biology (Vol. 3, pp. 1069–1069). Springer. https://doi.org/10.1007/978-1-4419-9863-7_604
View | DOI
 
2012 | Conference Paper | IST-REx-ID: 2825
Lampert, C. (2012). Dynamic pruning of factor graphs for maximum marginal prediction (Vol. 1, pp. 82–90). Presented at the NIPS: Neural Information Processing Systems, Lake Tahoe, NV, United States: Neural Information Processing Systems.
View
 
2012 | Journal Article | IST-REx-ID: 3164
Blaschko, M., & Lampert, C. (2012). Guest editorial: Special issue on structured prediction and inference. International Journal of Computer Vision. Springer. https://doi.org/10.1007/s11263-012-0530-y
View | DOI
 
2012 | Conference Paper | IST-REx-ID: 3125 | OA
Sharmanska, V., Quadrianto, N., & Lampert, C. (2012). Augmented attribute representations (Vol. 7576, pp. 242–255). Presented at the ECCV: European Conference on Computer Vision, Florence, Italy: Springer. https://doi.org/10.1007/978-3-642-33715-4_18
[Submitted Version] View | Files available | DOI
 
2012 | Conference Paper | IST-REx-ID: 3126
Müller, A., Nowozin, S., & Lampert, C. (2012). Information theoretic clustering using minimal spanning trees (Vol. 7476, pp. 205–215). Presented at the DAGM: German Association For Pattern Recognition, Graz, Austria: Springer. https://doi.org/10.1007/978-3-642-32717-9_21
View | DOI
 
2012 | Journal Article | IST-REx-ID: 3248 | OA
Lampert, C., & Peters, J. (2012). Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components. Journal of Real-Time Image Processing. Springer. https://doi.org/10.1007/s11554-010-0168-3
[Submitted Version] View | Files available | DOI
 
2012 | Conference Paper | IST-REx-ID: 3124 | OA
Korc, F., Kolmogorov, V., & Lampert, C. (2012). Approximating marginals using discrete energy minimization. Presented at the ICML: International Conference on Machine Learning, Edinburgh, Scotland: ICML.
[Submitted Version] View | Files available
 

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