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.

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.

Seed, expand and constrain: Three principles for weakly-supervised image segmentation
A. Kolesnikov, C. Lampert, in:, Springer, 2016, pp. 695–711.

Optimal geospatial allocation of volunteers for crisis management
J. Pielorz, C. Lampert, in:, IEEE, 2016.

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.

Theoretical foundations of multi-task lifelong learning
A. Pentina, Theoretical Foundations of Multi-Task Lifelong Learning, Institute of Science and Technology Austria, 2016.

Lifelong learning with non-i.i.d. tasks
A. Pentina, C. Lampert, in:, Neural Information Processing Systems, 2015, pp. 1540–1548.

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.

Novel plasticity rule can explain the development of sensorimotor intelligence
R. Der, G.S. Martius, PNAS 112 (2015) 24–32.

Multi-task and lifelong learning of kernels
A. Pentina, S. Ben David, in:, Springer, 2015, pp. 194–208.

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.

Classifier adaptation at prediction time
A. Royer, C. Lampert, in:, IEEE, 2015, pp. 1401–1409.

Predicting the future behavior of a time-varying probability distribution
C. Lampert, in:, IEEE, 2015, pp. 942–950.

Curriculum learning of multiple tasks
A. Pentina, V. Sharmanska, C. Lampert, in:, IEEE, 2015, pp. 5492–5500.

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.

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.

Quantifying emergent behavior of autonomous robots
G.S. Martius, E. Olbrich, Entropy 17 (2015) 7266–7297.

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.

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.

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.