Multi-task learning with labeled and unlabeled tasks
A. Pentina, C. Lampert, in:, ML Research Press, 2017, pp. 2807–2816.
LibreCat: https://research-explorer.ista.ac.at/record/999
WoS: 000683309502093

Lifelong learning with weighted majority votes
A. Pentina, R. Urner, in:, Neural Information Processing Systems, 2016, pp. 3619–3627.
LibreCat: https://research-explorer.ista.ac.at/record/1098

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.
LibreCat: https://research-explorer.ista.ac.at/record/1102
DOI: 10.5244/C.30.92

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.
LibreCat: https://research-explorer.ista.ac.at/record/1214
DOI: 10.1109/IROS.2016.7759138

Seed, expand and constrain: Three principles for weakly-supervised image segmentation
A. Kolesnikov, C. Lampert, in:, Springer, 2016, pp. 695–711.
LibreCat: https://research-explorer.ista.ac.at/record/1369
DOI: 10.1007/978-3-319-46493-0_42

Optimal geospatial allocation of volunteers for crisis management
J. Pielorz, C. Lampert, in:, IEEE, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/1707
DOI: 10.1109/ICT-DM.2015.7402041

Self-organized control of an tendon driven arm by differential extrinsic plasticity
G.S. Martius, R. Hostettler, A. Knoll, R. Der, in:, Proceedings of the Artificial Life Conference 2016, MIT Press, 2016, pp. 142–143.
LibreCat: https://research-explorer.ista.ac.at/record/8094
DOI: 10.7551/978-0-262-33936-0-ch029

Theoretical foundations of multi-task lifelong learning
A. Pentina, Theoretical Foundations of Multi-Task Lifelong Learning, Institute of Science and Technology Austria, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/1126
DOI: 10.15479/AT:ISTA:TH_776

Lifelong learning with non-i.i.d. tasks
A. Pentina, C. Lampert, in:, Neural Information Processing Systems, 2015, pp. 1540–1548.
LibreCat: https://research-explorer.ista.ac.at/record/1425

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.
LibreCat: https://research-explorer.ista.ac.at/record/1533
DOI: 10.1109/TCSVT.2014.2379972

Novel plasticity rule can explain the development of sensorimotor intelligence
R. Der, G.S. Martius, PNAS 112 (2015) 24–32.
LibreCat: https://research-explorer.ista.ac.at/record/1570
DOI: 10.1073/pnas.1508400112
PMID: 26504200

Multi-task and lifelong learning of kernels
A. Pentina, S. Ben David, in:, Springer, 2015, pp. 194–208.
LibreCat: https://research-explorer.ista.ac.at/record/1706
DOI: 10.1007/978-3-319-24486-0_13

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.
LibreCat: https://research-explorer.ista.ac.at/record/1859
DOI: 10.1109/CVPR.2015.7298890

Classifier adaptation at prediction time
A. Royer, C. Lampert, in:, IEEE, 2015, pp. 1401–1409.
LibreCat: https://research-explorer.ista.ac.at/record/1860
DOI: 10.1109/CVPR.2015.7298746

Predicting the future behavior of a time-varying probability distribution
C. Lampert, in:, IEEE, 2015, pp. 942–950.
LibreCat: https://research-explorer.ista.ac.at/record/1858
DOI: 10.1109/CVPR.2015.7298696
arXiv: 1406.5362

Curriculum learning of multiple tasks
A. Pentina, V. Sharmanska, C. Lampert, in:, IEEE, 2015, pp. 5492–5500.
LibreCat: https://research-explorer.ista.ac.at/record/1857
DOI: 10.1109/CVPR.2015.7299188

Quantifying self-organizing behavior of autonomous robots
G.S. Martius, E. Olbrich, in:, Proceedings of the 13th European Conference on Artificial Life, MIT Press, 2015, p. 78.
LibreCat: https://research-explorer.ista.ac.at/record/12881
DOI: 10.7551/978-0-262-33027-5-ch018

Learning with attributes for object recognition: Parametric and non-parametrics views
V. Sharmanska, Learning with Attributes for Object Recognition: Parametric and Non-Parametrics Views, Institute of Science and Technology Austria, 2015.
LibreCat: https://research-explorer.ista.ac.at/record/1401
DOI: 10.15479/at:ista:1401

Quantifying emergent behavior of autonomous robots
G.S. Martius, E. Olbrich, Entropy 17 (2015) 7266–7297.
LibreCat: https://research-explorer.ista.ac.at/record/1655
DOI: 10.3390/e17107266

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.
LibreCat: https://research-explorer.ista.ac.at/record/1829
DOI: 10.1007/978-3-319-03194-1_3