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77 Publications
2019 | Journal Article | IST-REx-ID: 6952 
Learning single-image 3D reconstruction by generative modelling of shape, pose and shading
P.M. Henderson, V. Ferrari, International Journal of Computer Vision (2019).
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P.M. Henderson, V. Ferrari, International Journal of Computer Vision (2019).
2019 | Book (Editor) | IST-REx-ID: 7171
Wie Maschinen lernen
K. Kersting, C. Lampert, C. Rothkopf, eds., Wie Maschinen Lernen, Springer Nature, 2019.
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K. Kersting, C. Lampert, C. Rothkopf, eds., Wie Maschinen Lernen, Springer Nature, 2019.
2019 | Conference Paper | IST-REx-ID: 6942
Strategy representation by decision trees with linear classifiers
P. Ashok, T. Brázdil, K. Chatterjee, J. Křetínský, C. Lampert, V. Toman, in:, 16th International Conference on Quantitative Evaluation of Systems, Springer Nature, 2019, pp. 109–128.
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| arXiv
P. Ashok, T. Brázdil, K. Chatterjee, J. Křetínský, C. Lampert, V. Toman, in:, 16th International Conference on Quantitative Evaluation of Systems, Springer Nature, 2019, pp. 109–128.
2019 | Conference Paper | IST-REx-ID: 6569
Towards understanding knowledge distillation
P. Bui Thi Mai, C. Lampert, in:, Proceedings of the 36th International Conference on Machine Learning, PMLR, 2019, pp. 5142–5151.
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P. Bui Thi Mai, C. Lampert, in:, Proceedings of the 36th International Conference on Machine Learning, PMLR, 2019, pp. 5142–5151.
2019 | Conference Paper | IST-REx-ID: 6590
Robust learning from untrusted sources
N.H. Konstantinov, C. Lampert, in:, Proceedings of the 36th International Conference on Machine Learning, n.d.
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| arXiv
N.H. Konstantinov, C. Lampert, in:, Proceedings of the 36th International Conference on Machine Learning, n.d.
2019 | Journal Article | IST-REx-ID: 6944
KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications
R. Sun, C. Lampert, International Journal of Computer Vision (2019).
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R. Sun, C. Lampert, International Journal of Computer Vision (2019).
2019 | Conference Paper | IST-REx-ID: 6482
KS(conf): A light-weight test if a ConvNet operates outside of Its specifications
R. Sun, C. Lampert, in:, Springer Nature, 2019, pp. 244–259.
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| arXiv
R. Sun, C. Lampert, in:, Springer Nature, 2019, pp. 244–259.
2018 | Journal Article | IST-REx-ID: 321
Guest editors' introduction to the special section on learning with Shared information for computer vision and multimedia analysis
T. Darrell, C. Lampert, N. Sebe, Y. Wu, Y. Yan, IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (2018) 1029–1031.
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T. Darrell, C. Lampert, N. Sebe, Y. Wu, Y. Yan, IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (2018) 1029–1031.
2018 | Conference Paper | IST-REx-ID: 6589
The convergence of sparsified gradient methods
D.-A. Alistarh, T. Hoefler, M. Johansson, N.H. Konstantinov, S. Khirirat, C. Renggli, in:, Advances in Neural Information Processing Systems 31, Neural information processing systems, 2018, pp. 5973–5983.
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| arXiv
D.-A. Alistarh, T. Hoefler, M. Johansson, N.H. Konstantinov, S. Khirirat, C. Renggli, in:, Advances in Neural Information Processing Systems 31, Neural information processing systems, 2018, pp. 5973–5983.
2018 | Conference Paper | IST-REx-ID: 6011
Data-dependent stability of stochastic gradient descent
I. Kuzborskij, C. Lampert, in:, Proceedings of the 35 Th International Conference on Machine Learning, International Machine Learning Society, 2018, pp. 2815–2824.
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| arXiv
I. Kuzborskij, C. Lampert, in:, Proceedings of the 35 Th International Conference on Machine Learning, International Machine Learning Society, 2018, pp. 2815–2824.
2018 | Journal Article | IST-REx-ID: 6554
Zero-shot learning - A comprehensive evaluation of the good, the bad and the ugly
Y. Xian, C. Lampert, B. Schiele, Z. Akata, IEEE Transactions on Pattern Analysis and Machine Intelligence (2018) 1–1.
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Y. Xian, C. Lampert, B. Schiele, Z. Akata, IEEE Transactions on Pattern Analysis and Machine Intelligence (2018) 1–1.
2018 | Journal Article | IST-REx-ID: 563
Estimating barriers to gene flow from distorted isolation-by-distance patterns
H. Ringbauer, A. Kolesnikov, D. Field, N.H. Barton, Genetics 208 (2018) 1231–1245.
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H. Ringbauer, A. Kolesnikov, D. Field, N.H. Barton, Genetics 208 (2018) 1231–1245.
2018 | Conference Paper | IST-REx-ID: 6012
Learning equations for extrapolation and control
S. Sahoo, C. Lampert, G.S. Martius, in:, Proceedings of the 35th International Conference on Machine Learning, International Machine Learning Society, 2018, pp. 4442–4450.
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| arXiv
S. Sahoo, C. Lampert, G.S. Martius, in:, Proceedings of the 35th International Conference on Machine Learning, International Machine Learning Society, 2018, pp. 4442–4450.
2018 | Thesis | IST-REx-ID: 68
Learning from dependent data
A. Zimin, Learning from Dependent Data, IST Austria, 2018.
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A. Zimin, Learning from Dependent Data, IST Austria, 2018.
2018 | Research Data | IST-REx-ID: 5584
Nonlinear decoding of a complex movie from the mammalian retina
S. Deny, O. Marre, V. Botella-Soler, G.S. Martius, G. Tkacik, Nonlinear Decoding of a Complex Movie from the Mammalian Retina, IST Austria, 2018.
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S. Deny, O. Marre, V. Botella-Soler, G.S. Martius, G. Tkacik, Nonlinear Decoding of a Complex Movie from the Mammalian Retina, IST Austria, 2018.
2018 | Thesis | IST-REx-ID: 197
Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images
A. Kolesnikov, Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images, IST Austria, 2018.
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A. Kolesnikov, Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images, IST Austria, 2018.
2017 | Conference Paper | IST-REx-ID: 911
Probabilistic image colorization
A. Royer, A. Kolesnikov, C. Lampert, in:, BMVA Press, n.d.
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A. Royer, A. Kolesnikov, C. Lampert, in:, BMVA Press, n.d.
2017 | Conference Paper | IST-REx-ID: 1000
PixelCNN models with auxiliary variables for natural image modeling
A. Kolesnikov, C. Lampert, in:, Omnipress, 2017, pp. 1905–1914.
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A. Kolesnikov, C. Lampert, in:, Omnipress, 2017, pp. 1905–1914.
2017 | Conference Paper | IST-REx-ID: 652
Dynamical self consistency leads to behavioral development and emergent social interactions in robots
R. Der, G.S. Martius, in:, IEEE, 2017.
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R. Der, G.S. Martius, in:, IEEE, 2017.
2017 | Conference Paper | IST-REx-ID: 6841
Extrapolation and learning equations
G.S. Martius, C. Lampert, in:, 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings, International Conference on Learning Representations, 2017.
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| arXiv
G.S. Martius, C. Lampert, in:, 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings, International Conference on Learning Representations, 2017.
2017 | Conference Paper | IST-REx-ID: 998
iCaRL: Incremental classifier and representation learning
S.A. Rebuffi, A. Kolesnikov, G. Sperl, C. Lampert, in:, IEEE, 2017, pp. 5533–5542.
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S.A. Rebuffi, A. Kolesnikov, G. Sperl, C. Lampert, in:, IEEE, 2017, pp. 5533–5542.
2017 | Conference Paper | IST-REx-ID: 999
Multi-task learning with labeled and unlabeled tasks
A. Pentina, C. Lampert, in:, Omnipress, 2017, pp. 2807–2816.
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A. Pentina, C. Lampert, in:, Omnipress, 2017, pp. 2807–2816.
2017 | Journal Article | IST-REx-ID: 658
Self organized behavior generation for musculoskeletal robots
R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017) 00008.
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R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017) 00008.
2017 | Conference Paper | IST-REx-ID: 1108
Learning theory for conditional risk minimization
A. Zimin, C. Lampert, in:, JMLR, Inc. and Microtome Publishing, 2017, pp. 213–222.
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A. Zimin, C. Lampert, in:, JMLR, Inc. and Microtome Publishing, 2017, pp. 213–222.
2017 | Conference Paper | IST-REx-ID: 750
Optimal geospatial volunteer allocation needs realistic distances
J. Pielorz, M. Prandtstetter, M. Straub, C. Lampert, in:, 2017 IEEE International Conference on Big Data, IEEE, 2017, pp. 3760–3763.
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J. Pielorz, M. Prandtstetter, M. Straub, C. Lampert, in:, 2017 IEEE International Conference on Big Data, IEEE, 2017, pp. 3760–3763.
2016 | Conference Paper | IST-REx-ID: 1369
Seed, expand and constrain: Three principles for weakly-supervised image segmentation
A. Kolesnikov, C. Lampert, in:, Springer, 2016, pp. 695–711.
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A. Kolesnikov, C. Lampert, in:, Springer, 2016, pp. 695–711.
2016 | Conference Paper | IST-REx-ID: 1098
Lifelong learning with weighted majority votes
A. Pentina, R. Urner, in:, Neural Information Processing Systems, 2016, pp. 3619–3627.
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A. Pentina, R. Urner, in:, Neural Information Processing Systems, 2016, pp. 3619–3627.
2016 | Conference Paper | IST-REx-ID: 1214
Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm
G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, IEEE, 2016.
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G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, IEEE, 2016.
2016 | Conference Paper | IST-REx-ID: 1707
Optimal geospatial allocation of volunteers for crisis management
J. Pielorz, C. Lampert, in:, IEEE, 2016.
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J. Pielorz, C. Lampert, in:, IEEE, 2016.
2016 | Conference Paper | IST-REx-ID: 1102
Improving weakly-supervised object localization by micro-annotation
A. Kolesnikov, C. Lampert, in:, Proceedings of the British Machine Vision Conference 2016, BMVA Press, 2016, p. 92.1-92.12.
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A. Kolesnikov, C. Lampert, in:, Proceedings of the British Machine Vision Conference 2016, BMVA Press, 2016, p. 92.1-92.12.
2016 | Thesis | IST-REx-ID: 1126
Theoretical foundations of multi-task lifelong learning
A. Pentina, Theoretical Foundations of Multi-Task Lifelong Learning, IST Austria, 2016.
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A. Pentina, Theoretical Foundations of Multi-Task Lifelong Learning, IST Austria, 2016.
2015 | Journal Article | IST-REx-ID: 1655
Quantifying emergent behavior of autonomous robots
G.S. Martius, E. Olbrich, Entropy 17 (2015) 7266–7297.
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G.S. Martius, E. Olbrich, Entropy 17 (2015) 7266–7297.
2015 | Conference Paper | IST-REx-ID: 1706
Multi-task and lifelong learning of kernels
A. Pentina, S. Ben David, in:, Springer, 2015, pp. 194–208.
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A. Pentina, S. Ben David, in:, Springer, 2015, pp. 194–208.
2015 | Conference Paper | IST-REx-ID: 1857
Curriculum learning of multiple tasks
A. Pentina, V. Sharmanska, C. Lampert, in:, IEEE, 2015, pp. 5492–5500.
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A. Pentina, V. Sharmanska, C. Lampert, in:, IEEE, 2015, pp. 5492–5500.
2015 | Conference Paper | IST-REx-ID: 1858
Predicting the future behavior of a time-varying probability distribution
C. Lampert, in:, IEEE, 2015, pp. 942–950.
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| arXiv
C. Lampert, in:, IEEE, 2015, pp. 942–950.
2015 | Conference Paper | IST-REx-ID: 1860
Classifier adaptation at prediction time
A. Royer, C. Lampert, in:, IEEE, 2015, pp. 1401–1409.
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A. Royer, C. Lampert, in:, IEEE, 2015, pp. 1401–1409.
2015 | Journal Article | IST-REx-ID: 1570
Novel plasticity rule can explain the development of sensorimotor intelligence
R. Der, G.S. Martius, PNAS 112 (2015) E6224–E6232.
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| PubMed | Europe PMC
R. Der, G.S. Martius, PNAS 112 (2015) E6224–E6232.
2015 | Conference Paper | IST-REx-ID: 1859
A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle
N. Shah, V. Kolmogorov, C. Lampert, in:, IEEE, 2015, pp. 2737–2745.
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N. Shah, V. Kolmogorov, C. Lampert, in:, IEEE, 2015, pp. 2737–2745.
2015 | Conference Paper | IST-REx-ID: 1425
Lifelong learning with non-i.i.d. tasks
A. Pentina, C. Lampert, in:, Neural Information Processing Systems, 2015, pp. 1540–1548.
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A. Pentina, C. Lampert, in:, Neural Information Processing Systems, 2015, pp. 1540–1548.
2015 | Thesis | IST-REx-ID: 1401
Learning with attributes for object recognition: Parametric and non-parametrics views
V. Sharmanska, Learning with Attributes for Object Recognition: Parametric and Non-Parametrics Views, IST Austria, 2015.
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V. Sharmanska, Learning with Attributes for Object Recognition: Parametric and Non-Parametrics Views, IST Austria, 2015.
2015 | Journal Article | IST-REx-ID: 1533
Segmentation over detection via optimal sparse reconstructions
W. Xia, C. Domokos, J. Xiong, L. Cheong, S. Yan, IEEE Transactions on Circuits and Systems for Video Technology 25 (2015) 1295–1308.
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W. Xia, C. Domokos, J. Xiong, L. Cheong, S. Yan, IEEE Transactions on Circuits and Systems for Video Technology 25 (2015) 1295–1308.
2014 | Conference Paper | IST-REx-ID: 2171
Closed-form approximate CRF training for scalable image segmentation
A. Kolesnikov, M. Guillaumin, V. Ferrari, C. Lampert, 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), Springer, 2014, pp. 550–565.
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A. Kolesnikov, M. Guillaumin, V. Ferrari, C. Lampert, 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), Springer, 2014, pp. 550–565.
2014 | Conference Paper | IST-REx-ID: 2033
Mind the nuisance: Gaussian process classification using privileged noise
D. Hernandez Lobato, V. Sharmanska, K. Kersting, C. Lampert, N. Quadrianto, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems, 2014, pp. 837–845.
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D. Hernandez Lobato, V. Sharmanska, K. Kersting, C. Lampert, N. Quadrianto, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems, 2014, pp. 837–845.
2014 | Conference Paper | IST-REx-ID: 2057
Majority vote of diverse classifiers for late fusion
E. Morvant, A. Habrard, S. Ayache, in:, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, 2014, pp. 153–162.
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E. Morvant, A. Habrard, S. Ayache, in:, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, 2014, pp. 153–162.
2014 | Conference Paper | IST-REx-ID: 2172
Deep Fisher Kernels – End to end learning of the Fisher Kernel GMM parameters
V. Sydorov, M. Sakurada, C. Lampert, in:, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 2014, pp. 1402–1409.
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V. Sydorov, M. Sakurada, C. Lampert, in:, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 2014, pp. 1402–1409.
2014 | Conference Paper | IST-REx-ID: 2189
Adaptation de domaine de vote de majorité par auto-étiquetage non itératif
E. Morvant, in:, Elsevier, 2014, pp. 49–58.
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E. Morvant, in:, Elsevier, 2014, pp. 49–58.
2014 | Conference Paper | IST-REx-ID: 2160
A PAC-Bayesian bound for Lifelong Learning
A. Pentina, C. Lampert, in:, E. Xing, T. Jebara (Eds.), Omnipress, 2014, pp. 991–999.
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A. Pentina, C. Lampert, in:, E. Xing, T. Jebara (Eds.), Omnipress, 2014, pp. 991–999.
2014 | Conference Paper | IST-REx-ID: 2173
CoConut: Co-classification with output space regularization
S. Khamis, C. Lampert, in:, Proceedings of the British Machine Vision Conference 2014, BMVA Press, 2014.
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S. Khamis, C. Lampert, in:, Proceedings of the British Machine Vision Conference 2014, BMVA Press, 2014.
2014 | Journal Article | IST-REx-ID: 2180
Learning a priori constrained weighted majority votes
A. Bellet, A. Habrard, E. Morvant, M. Sebban, Machine Learning 97 (2014) 129–154.
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A. Bellet, A. Habrard, E. Morvant, M. Sebban, Machine Learning 97 (2014) 129–154.
2014 | Book Chapter | IST-REx-ID: 1829
Movement templates for learning of hitting and batting
K. Muelling, O. Kroemer, C. Lampert, B. Schölkopf, in:, J. Kober, J. Peters (Eds.), Learning Motor Skills, Springer, 2014, pp. 69–82.
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K. Muelling, O. Kroemer, C. Lampert, B. Schölkopf, in:, J. Kober, J. Peters (Eds.), Learning Motor Skills, Springer, 2014, pp. 69–82.