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3161 Publications
2014 | Journal Article | IST-REx-ID: 2158 | 
R. Majumdar, M. K. Sixt, and C. Parent, “New paradigms in the establishment and maintenance of gradients during directed cell migration,” Current Opinion in Cell Biology, vol. 30, no. 1. Elsevier, pp. 33–40, 2014.
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| PubMed | Europe PMC
2014 | Conference Paper | IST-REx-ID: 2160 |
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: 2162 |
K. Chatterjee and R. Ibsen-Jensen, “The complexity of ergodic mean payoff games,” presented at the ICST: International Conference on Software Testing, Verification and Validation, Copenhagen, Denmark, 2014, vol. 8573, no. Part 2, pp. 122–133.
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| arXiv
2014 | Conference Paper | IST-REx-ID: 2163 |
K. Chatterjee and L. Doyen, “Games with a weak adversary,” in Lecture Notes in Computer Science, Copenhagen, Denmark, 2014, vol. 8573, no. Part 2, pp. 110–121.
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| arXiv
2014 | Conference Paper | IST-REx-ID: 2167 |
P. Daca, T. A. Henzinger, W. Krenn, and D. Nickovic, “Compositional specifications for IOCO testing,” in IEEE 7th International Conference on Software Testing, Verification and Validation, Cleveland, USA, 2014.
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| arXiv
2014 | Journal Article | IST-REx-ID: 2168 |
J. Kelleher, A. Etheridge, and N. H. Barton, “Coalescent simulation in continuous space: Algorithms for large neighbourhood size,” Theoretical Population Biology, vol. 95. Academic Press, pp. 13–23, 2014.
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2014 | Journal Article | IST-REx-ID: 2169 |
N. H. Barton, S. Novak, and T. Paixao, “Diverse forms of selection in evolution and computer science,” PNAS, vol. 111, no. 29. National Academy of Sciences, pp. 10398–10399, 2014.
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2014 | Conference Paper | IST-REx-ID: 2171 |
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: 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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