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Emerging category representation in the visual forebrain hierarchy of pigeons ( Columba livia )Azizi, A. H., Pusch, R., Koenen, C., Klatt, S., Bröcker, F., Thiele, S., et al.Behavioural Brain Research
@article{AziziPuschKoenenEtAl2018, author = {Azizi, Amir Hossein and Pusch, Roland and Koenen, Charlotte and Klatt, Sebastian and Bröcker, Franziska and Thiele, Samuel and Kellermann, Janosch and Güntürkün, Onur and Cheng, Sen}, title = {Emerging category representation in the visual forebrain hierarchy of pigeons ( Columba livia )}, journal = {Behavioural Brain Research}, month = {June}, year = {2018}, doi = {10.1016/j.bbr.2018.05.014}, }Azizi, A. H., Pusch, R., Koenen, C., Klatt, S., Bröcker, F., Thiele, S., et al. (2018). Emerging category representation in the visual forebrain hierarchy of pigeons ( Columba livia ). Behavioural Brain Research. http://doi.org/10.1016/j.bbr.2018.05.014The reduction of adult neurogenesis in depression impairs the retrieval of new as well as remote episodic memoryFang, J., Demic, S., & Cheng, S.PLOS ONE, 13(6), e0198406@article{FangDemicCheng2018, author = {Fang, Jing and Demic, Selver and Cheng, Sen}, title = {The reduction of adult neurogenesis in depression impairs the retrieval of new as well as remote episodic memory}, journal = {PLOS ONE}, volume = {13}, number = {6}, pages = {e0198406}, month = {June}, year = {2018}, doi = {10.1371/journal.pone.0198406}, }Fang, J., Demic, S., & Cheng, S.. (2018). The reduction of adult neurogenesis in depression impairs the retrieval of new as well as remote episodic memory. PLOS ONE, 13(6), e0198406. http://doi.org/10.1371/journal.pone.0198406TMS-induced neuronal plasticity enables targeted remodeling of visual cortical mapsKozyrev, V., Staadt, R., Eysel, U. T., & Jancke, D.Proceedings of the National Academy of Sciences, 115(25), 6476–6481@article{KozyrevStaadtEyselEtAl2018, author = {Kozyrev, Vladislav and Staadt, Robert and Eysel, Ulf T. and Jancke, Dirk}, title = {TMS-induced neuronal plasticity enables targeted remodeling of visual cortical maps}, journal = {Proceedings of the National Academy of Sciences}, volume = {115}, number = {25}, pages = {6476–6481}, month = {June}, year = {2018}, doi = {10.1073/pnas.1802798115}, }Kozyrev, V., Staadt, R., Eysel, U. T., & Jancke, D.. (2018). TMS-induced neuronal plasticity enables targeted remodeling of visual cortical maps. Proceedings of the National Academy of Sciences, 115(25), 6476–6481. http://doi.org/10.1073/pnas.1802798115The Interaction between Semantic Representation and Episodic MemoryFang, J., Rüther, N., Bellebaum, C., Wiskott, L., & Cheng, S.Neural Computation, 30(2), 293–332@article{FangRütherBellebaumEtAl2018, author = {Fang, Jing and Rüther, Naima and Bellebaum, Christian and Wiskott, Laurenz and Cheng, Sen}, title = {The Interaction between Semantic Representation and Episodic Memory}, journal = {Neural Computation}, volume = {30}, number = {2}, pages = {293–332}, month = {February}, year = {2018}, doi = {10.1162/neco_a_01044}, }Fang, J., Rüther, N., Bellebaum, C., Wiskott, L., & Cheng, S.. (2018). The Interaction between Semantic Representation and Episodic Memory. Neural Computation, 30(2), 293–332. http://doi.org/10.1162/neco_a_01044Drift Theory in Continuous Search Spaces: Expected Hitting Time of the (1+1)-ES with 1/5 Success RuleAkimoto, Y., Auger, A., & Glasmachers, T.In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) ACM@inproceedings{AkimotoAugerGlasmachers2018, author = {Akimoto, Youhei and Auger, Anne and Glasmachers, Tobias}, title = {Drift Theory in Continuous Search Spaces: Expected Hitting Time of the (1+1)-ES with 1/5 Success Rule}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)}, publisher = {ACM}, year = {2018}, }Akimoto, Y., Auger, A., & Glasmachers, T.. (2018). Drift Theory in Continuous Search Spaces: Expected Hitting Time of the (1+1)-ES with 1/5 Success Rule. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO). ACM.Fine-Grained Vehicle Representations for Autonomous DrivingBarowski, T., Szczot, M., & Houben, S.In Accepted for IEEE International Conference on Intelligent Transportation Systems (ITSC)@inproceedings{BarowskiSzczotHouben2018, author = {Barowski, Thomas and Szczot, Magdalena and Houben, Sebastian}, title = {Fine-Grained Vehicle Representations for Autonomous Driving}, booktitle = {Accepted for IEEE International Conference on Intelligent Transportation Systems (ITSC)}, year = {2018}, }Barowski, T., Szczot, M., & Houben, S.. (2018). Fine-Grained Vehicle Representations for Autonomous Driving. In Accepted for IEEE International Conference on Intelligent Transportation Systems (ITSC).Self-improving System Integration – Status and Challenges After Five Years of SISSYBellman, K., Botev, J., Diaconescu, A., Esterle, L., Gruhl, C., Landauer, C., et al.In Proceedings of IEEE International Workshops on Foundations and Applications of Self* Systems@inproceedings{BellmanBotevDiaconescuEtAl2018, author = {Bellman, Kirstie and Botev, Jean and Diaconescu, Ada and Esterle, Lukas and Gruhl, Christian and Landauer, Chris and Lewis, Peter R. and Anthony Stein, and Tomforde, Sven and Würtz, Rolf P.}, title = {Self-improving System Integration – Status and Challenges After Five Years of SISSY}, booktitle = {Proceedings of IEEE International Workshops on Foundations and Applications of Self* Systems}, year = {2018}, }Bellman, K., Botev, J., Diaconescu, A., Esterle, L., Gruhl, C., Landauer, C., et al. (2018). Self-improving System Integration – Status and Challenges After Five Years of SISSY. In Proceedings of IEEE International Workshops on Foundations and Applications of Self* Systems.Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section SearchGlasmachers, T., & Qaadan, S.In G. Nicosia, Pardalos, P., Giuffrida, G., Umeton, R., & Sciacca, V. (Eds.), The 4th International Conference on machine Learning, Optimization and Data science - LOD 2018@inproceedings{GlasmachersQaadan2018, author = {Glasmachers, Tobias and Qaadan, Sahar}, title = {Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search}, booktitle = {The 4th International Conference on machine Learning, Optimization and Data science - LOD 2018}, editor = {Nicosia, Giuseppe and Pardalos, Panos and Giuffrida, Giovanni and Umeton, Renato and Sciacca, Vincenzo}, year = {2018}, }Glasmachers, T., & Qaadan, S.. (2018). Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search. In G. Nicosia, Pardalos, P., Giuffrida, G., Umeton, R., & Sciacca, V. (Eds.), The 4th International Conference on machine Learning, Optimization and Data science - LOD 2018.Sequences of discrete attentional shifts emerge from a neural dynamic architecture for conjunctive visual search that operates in continuous timeGrieben, R., Tekülve, J., Zibner, S. K. U., Schneegans, S., & Schöner, G.In T. T. Rogers, Rau, M., Zhu, X., & Kalish, C. W. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 429–434)@inproceedings{GriebenTekülveZibnerEtAl2018, author = {Grieben, R and Tekülve, J. and Zibner, S.K.U. and Schneegans, S. and Schöner, G.}, title = {Sequences of discrete attentional shifts emerge from a neural dynamic architecture for conjunctive visual search that operates in continuous time}, booktitle = {Proceedings of the 40th Annual Conference of the Cognitive Science Society}, editor = {Rogers, T.T. and Rau, M. and Zhu, X. and Kalish, C. W.}, pages = {429–434}, year = {2018}, }Grieben, R., Tekülve, J., Zibner, S. K. U., Schneegans, S., & Schöner, G.. (2018). Sequences of discrete attentional shifts emerge from a neural dynamic architecture for conjunctive visual search that operates in continuous time. In T. T. Rogers, Rau, M., Zhu, X., & Kalish, C. W. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 429–434).Anticipatory coarticulation in non-speeded arm movements can be motor-equivalent, carry-over coarticulation always isHansen, E., Grimme, B., Reimann, H., & Schöner, G.Experimental Brain Research@article{HansenGrimmeReimannEtAl2018, author = {Hansen, Eva and Grimme, Britta and Reimann, Hendrik and Schöner, Gregor}, title = {Anticipatory coarticulation in non-speeded arm movements can be motor-equivalent, carry-over coarticulation always is}, journal = {Experimental Brain Research}, year = {2018}, doi = {10.1007/s00221-018-5215-5}, }Hansen, E., Grimme, B., Reimann, H., & Schöner, G.. (2018). Anticipatory coarticulation in non-speeded arm movements can be motor-equivalent, carry-over coarticulation always is. Experimental Brain Research. http://doi.org/10.1007/s00221-018-5215-5Evaluation of Synthetic Video Data in Machine Learning Approaches for Parking Space ClassificationHorn, D., & Houben, S.In IEEE Intelligent Vehicles Symposium (IV) (pp. 2157–2162)@inproceedings{HornHouben2018, author = {Horn, Daniela and Houben, Sebastian}, title = {Evaluation of Synthetic Video Data in Machine Learning Approaches for Parking Space Classification}, booktitle = {IEEE Intelligent Vehicles Symposium (IV)}, pages = {2157–2162}, year = {2018}, }Horn, D., & Houben, S.. (2018). Evaluation of Synthetic Video Data in Machine Learning Approaches for Parking Space Classification. In IEEE Intelligent Vehicles Symposium (IV) (pp. 2157–2162).Automatisierte VideoanalyseHorn, D., Ibisch, A., & Tschentscher, M.In C. Moritz & Corsten, M. (Eds.), Handbuch Qualitative Videoanalyse (pp. 445–456) Springer VS Verlag@incollection{HornIbischTschentscher2018, author = {Horn, D. and Ibisch, A. and Tschentscher, M.}, title = {Automatisierte Videoanalyse}, booktitle = {Handbuch Qualitative Videoanalyse}, editor = {Moritz, C. and Corsten, M.}, pages = {445–456}, publisher = {Springer VS Verlag}, year = {2018}, }Horn, D., Ibisch, A., & Tschentscher, M.. (2018). Automatisierte Videoanalyse. In C. Moritz & Corsten, M. (Eds.), Handbuch Qualitative Videoanalyse (pp. 445–456). Springer VS Verlag.A Neural Dynamic Architecture That Autonomously Builds Mental ModelsKounatidou, P., Richter, M., & Schöner, G.In T. T. Rogers, Rau, M., Zhu, X., & Kalish, C. W. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 643–648)@inproceedings{KounatidouRichterSchöner2018, author = {Kounatidou, P. and Richter, M. and Schöner, G.}, title = {A Neural Dynamic Architecture That Autonomously Builds Mental Models}, booktitle = {Proceedings of the 40th Annual Conference of the Cognitive Science Society}, editor = {Rogers, T.T. and Rau, M. and Zhu, X. and Kalish, C. W.}, pages = {643–648}, year = {2018}, }Kounatidou, P., Richter, M., & Schöner, G.. (2018). A Neural Dynamic Architecture That Autonomously Builds Mental Models. In T. T. Rogers, Rau, M., Zhu, X., & Kalish, C. W. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 643–648).Challenges in High-dimensional Controller Design with Evolution StrategiesMüller, N., & Glasmachers, T.In Parallel Problem Solving from Nature (PPSN XVI) Springer@inproceedings{MüllerGlasmachers2018, author = {Müller, Nils and Glasmachers, Tobias}, title = {Challenges in High-dimensional Controller Design with Evolution Strategies}, booktitle = {Parallel Problem Solving from Nature (PPSN XVI)}, publisher = {Springer}, year = {2018}, }Müller, N., & Glasmachers, T.. (2018). Challenges in High-dimensional Controller Design with Evolution Strategies. In Parallel Problem Solving from Nature (PPSN XVI). Springer.Organic Face Graph ClassificationNilkens, A.In S. Tomforde & Sick, B. (Eds.), Organic Computing: Doctoral Dissertation Colloquium 2017 (Vol. 11, pp. 79–92) kassel university press GmbH@inproceedings{Nilkens2018, author = {Nilkens, Andreas}, title = {Organic Face Graph Classification}, booktitle = {Organic Computing: Doctoral Dissertation Colloquium 2017}, editor = {Tomforde, Sven and Sick, Bernhard}, pages = {79–92}, publisher = {kassel university press GmbH}, volume = {11}, year = {2018}, }Nilkens, A. (2018). Organic Face Graph Classification. In S. Tomforde & Sick, B. (Eds.), Organic Computing: Doctoral Dissertation Colloquium 2017 (Vol. 11, pp. 79–92). kassel university press GmbH.Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM TrainingQaadan, S., & Glasmachers, T.arXiv.org@techreport{QaadanGlasmachers2018, author = {Qaadan, Sahar and Glasmachers, Tobias}, title = {Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM Training}, institution = {arXiv.org}, number = {arXiv:1806.10179}, year = {2018}, }Qaadan, S., & Glasmachers, T.. (2018). Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM Training (No. arXiv:1806.10179). arXiv.org.Dual SVM Training on a BudgetQaadan, S., Schüler, M., & Glasmachers, T.arXiv.org@techreport{QaadanSchülerGlasmachers2018, author = {Qaadan, Sahar and Schüler, Merlin and Glasmachers, Tobias}, title = {Dual SVM Training on a Budget}, institution = {arXiv.org}, number = {arXiv:1806.10182}, year = {2018}, }Qaadan, S., Schüler, M., & Glasmachers, T.. (2018). Dual SVM Training on a Budget (No. arXiv:1806.10182). arXiv.org.Unsupervised Acquisition of Human Body ModelsWalther, T., & Würtz, R. P.Cognitive Systems Research, 47, 68–84@article{WaltherWürtz2018, author = {Walther, Thomas and Würtz, Rolf P.}, title = {Unsupervised Acquisition of Human Body Models}, journal = {Cognitive Systems Research}, volume = {47}, pages = {68–84}, year = {2018}, doi = {10.1016/j.cogsys.2017.08.001}, }Walther, T., & Würtz, R. P.. (2018). Unsupervised Acquisition of Human Body Models. Cognitive Systems Research, 47, 68–84. http://doi.org/10.1016/j.cogsys.2017.08.001Slowness as a Proxy for Temporal Predictability: An Empirical ComparisonWeghenkel, B., & Wiskott, L.Neural Computation, 30(5), 1151–1179@article{WeghenkelWiskott2018, author = {Weghenkel, Björn and Wiskott, Laurenz}, title = {Slowness as a Proxy for Temporal Predictability: An Empirical Comparison}, journal = {Neural Computation}, volume = {30}, number = {5}, pages = {1151–1179}, year = {2018}, doi = {10.1162/neco_a_01070}, }Weghenkel, B., & Wiskott, L.. (2018). Slowness as a Proxy for Temporal Predictability: An Empirical Comparison. Neural Computation, 30(5), 1151–1179. http://doi.org/10.1162/neco_a_01070Doing without metarepresentation: Scenario construction explains the epistemic generativity and privileged status of episodic memoryWerning, M., & Cheng, S.Behavioral and Brain Sciences, 41@article{WerningCheng2018, author = {Werning, Markus and Cheng, Sen}, title = {Doing without metarepresentation: Scenario construction explains the epistemic generativity and privileged status of episodic memory}, journal = {Behavioral and Brain Sciences}, volume = {41}, year = {2018}, doi = {10.1017/s0140525x17001534}, }Werning, M., & Cheng, S.. (2018). Doing without metarepresentation: Scenario construction explains the epistemic generativity and privileged status of episodic memory. Behavioral and Brain Sciences, 41. http://doi.org/10.1017/s0140525x17001534Interactive Learning Without Ground TruthWürtz, R. P., Tomforde, S., Calma, A., Kottke, D., & Sick, B.In S. Tomforde & Sick, B. (Eds.), Organic Computing: Doctoral Dissertation Colloquium 2017 (Vol. 11, p. II.1–II.4) kassel university press GmbH@inproceedings{WürtzTomfordeCalmaEtAl2018, author = {Würtz, Rolf P. and Tomforde, Sven and Calma, Adrian and Kottke, Daniel and Sick, Bernhard}, title = {Interactive Learning Without Ground Truth}, booktitle = {Organic Computing: Doctoral Dissertation Colloquium 2017}, editor = {Tomforde, Sven and Sick, Bernhard}, pages = {II.1–II.4}, publisher = {kassel university press GmbH}, volume = {11}, year = {2018}, }Würtz, R. P., Tomforde, S., Calma, A., Kottke, D., & Sick, B. (2018). Interactive Learning Without Ground Truth. In S. Tomforde & Sick, B. (Eds.), Organic Computing: Doctoral Dissertation Colloquium 2017 (Vol. 11, p. II.1–II.4). kassel university press GmbH.2017
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Unsupervised Acquisition of Human Body Models using Principles of Organic ComputingWalther, T., & Würtz, R. P.ArXiv e-prints
@article{WaltherWürtz2017, author = {Walther, Thomas and Würtz, Rolf P.}, title = {Unsupervised Acquisition of Human Body Models using Principles of Organic Computing}, journal = {ArXiv e-prints}, month = {April}, year = {2017}, }Walther, T., & Würtz, R. P.. (2017). Unsupervised Acquisition of Human Body Models using Principles of Organic Computing. ArXiv e-prints. Retrieved from http://arxiv.org/abs/1704.03724A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line UpdatingKnips, G., Zibner, S. K. U., Reimann, H., & Schöner, G.Frontiers in Neurorobotics, 11(March), 9:1–14@article{KnipsZibnerReimannEtAl2017, author = {Knips, Guido and Zibner, Stephan K U and Reimann, Hendrik and Schöner, Gregor}, title = {A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating}, journal = {Frontiers in Neurorobotics}, volume = {11}, number = {March}, pages = {9:1–14}, month = {March}, year = {2017}, doi = {10.3389/fnbot.2017.00009}, }Knips, G., Zibner, S. K. U., Reimann, H., & Schöner, G.. (2017). A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating. Frontiers in Neurorobotics, 11(March), 9:1–14. http://doi.org/10.3389/fnbot.2017.00009Gaussian-binary restricted Boltzmann machines for modeling natural image statisticsMelchior, J., Wang, N., & Wiskott, L.PLOS ONE, 12(2), 1–24@article{MelchiorWangWiskott2017, author = {Melchior, Jan and Wang, Nan and Wiskott, Laurenz}, title = {Gaussian-binary restricted Boltzmann machines for modeling natural image statistics}, journal = {PLOS ONE}, volume = {12}, number = {2}, pages = {1–24}, month = {February}, year = {2017}, doi = {10.1371/journal.pone.0171015}, }Melchior, J., Wang, N., & Wiskott, L.. (2017). Gaussian-binary restricted Boltzmann machines for modeling natural image statistics. PLOS ONE, 12(2), 1–24. http://doi.org/10.1371/journal.pone.0171015Generating sequences in recurrent neural networks for storing and retrieving episodic memoriesBayati, M., Melchior, J., Wiskott, L., & Cheng, S.In Proc. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2@inproceedings{BayatiMelchiorWiskottEtAl2017, author = {Bayati, Mehdi and Melchior, Jan and Wiskott, Laurenz and Cheng, Sen}, title = {Generating sequences in recurrent neural networks for storing and retrieving episodic memories}, booktitle = {Proc. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2}, year = {2017}, }Bayati, M., Melchior, J., Wiskott, L., & Cheng, S.. (2017). Generating sequences in recurrent neural networks for storing and retrieving episodic memories. In Proc. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2. Retrieved from http://europepmc.org/articles/PMC5592442Gedächtnisverbesserung: Möglichkeiten und kritische BetrachtungCheng, S.In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze . Diskurse des Transhumanismus. (p. invited contribution) Bielefeld: transcript Verlag@incollection{Cheng2017, author = {Cheng, Sen}, title = {Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung}, booktitle = {Die Grenze . Diskurse des Transhumanismus.}, editor = {Hüttemann, Felix and Liggieri, Kevin}, pages = {invited contribution}, publisher = {transcript Verlag}, address = {Bielefeld}, year = {2017}, }Cheng, S. (2017). Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung. In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze . Diskurse des Transhumanismus. (p. invited contribution). Bielefeld: transcript Verlag.Consolidation of Episodic Memory: An Epiphenomenon of Semantic LearningCheng, S.In N. Axmacher & Rasch, B. (Eds.), Cognitive Neuroscience of Memory Consolidation (pp. 57–72) Cham, Switzerland: Springer International Publishing@incollection{Cheng2017b, author = {Cheng, Sen}, title = {Consolidation of Episodic Memory: An Epiphenomenon of Semantic Learning}, booktitle = {Cognitive Neuroscience of Memory Consolidation}, editor = {Axmacher, Nikolai and Rasch, Björn}, pages = {57–72}, publisher = {Springer International Publishing}, chapter = {4}, address = {Cham, Switzerland}, year = {2017}, doi = {10.1007/978-3-319-45066-7_4}, }Cheng, S. (2017). Consolidation of Episodic Memory: An Epiphenomenon of Semantic Learning. In N. Axmacher & Rasch, B. (Eds.), Cognitive Neuroscience of Memory Consolidation (pp. 57–72). Cham, Switzerland: Springer International Publishing. http://doi.org/10.1007/978-3-319-45066-7_4Experience-Dependency of Reliance on Local Visual and Idiothetic Cues for Spatial Representations Created in the Absence of Distal InformationDraht, F., Zhang, S., Rayan, A., Schönfeld, F., Wiskott, L., & Manahan-Vaughan, D.Frontiers in Behavioral Neuroscience, 11(92)@article{DrahtZhangRayanEtAl2017, author = {Draht, Fabian and Zhang, Sijie and Rayan, Abdelrahman and Schönfeld, Fabian and Wiskott, Laurenz and Manahan-Vaughan, Denise}, title = {Experience-Dependency of Reliance on Local Visual and Idiothetic Cues for Spatial Representations Created in the Absence of Distal Information}, journal = {Frontiers in Behavioral Neuroscience}, volume = {11}, number = {92}, year = {2017}, doi = {10.3389/fnbeh.2017.00092}, }Draht, F., Zhang, S., Rayan, A., Schönfeld, F., Wiskott, L., & Manahan-Vaughan, D. (2017). Experience-Dependency of Reliance on Local Visual and Idiothetic Cues for Spatial Representations Created in the Absence of Distal Information. Frontiers in Behavioral Neuroscience, 11(92). http://doi.org/10.3389/fnbeh.2017.00092Extensions of Hierarchical Slow Feature Analysis for Efficient Classification and Regression on High-Dimensional DataEscalante-B., A. N.Doctoral thesis, Ruhr University Bochum, Faculty of Electrical Engineering and Information Technology@phdthesis{Escalante-B.2017, author = {Escalante-B., Alberto N.}, title = {Extensions of Hierarchical Slow Feature Analysis for Efficient Classification and Regression on High-Dimensional Data}, school = {Ruhr University Bochum, Faculty of Electrical Engineering and Information Technology}, year = {2017}, }Escalante-B., A. N. (2017). Extensions of Hierarchical Slow Feature Analysis for Efficient Classification and Regression on High-Dimensional Data. Doctoral thesis, Ruhr University Bochum, Faculty of Electrical Engineering and Information Technology.A Fast Incremental BSP Tree Archive for Non-dominated PointsGlasmachers, T.In Evolutionary Multi-Criterion Optimization (EMO) Springer@inproceedings{Glasmachers2017, author = {Glasmachers, T.}, title = {A Fast Incremental BSP Tree Archive for Non-dominated Points}, booktitle = {Evolutionary Multi-Criterion Optimization (EMO)}, publisher = {Springer}, year = {2017}, }Glasmachers, T. (2017). A Fast Incremental BSP Tree Archive for Non-dominated Points. In Evolutionary Multi-Criterion Optimization (EMO). Springer.Limits of End-to-End LearningGlasmachers, T.In Proceedings of the 9th Asian Conference on Machine Learning (ACML)@inproceedings{Glasmachers2017b, author = {Glasmachers, T.}, title = {Limits of End-to-End Learning}, booktitle = {Proceedings of the 9th Asian Conference on Machine Learning (ACML)}, year = {2017}, }Glasmachers, T. (2017). Limits of End-to-End Learning. In Proceedings of the 9th Asian Conference on Machine Learning (ACML).Global Convergence of the (1+1) Evolution StrategyGlasmachers, T.arxiv.org@techreport{Glasmachers2017c, author = {Glasmachers, T.}, title = {Global Convergence of the (1+1) Evolution Strategy}, institution = {arxiv.org}, number = {arxiv:1706.02887}, year = {2017}, }Glasmachers, T. (2017). Global Convergence of the (1+1) Evolution Strategy (No. arxiv:1706.02887). arxiv.org.Cue Integration by Similarity Rank List Coding — Application to Invariant Object RecognitionGrieben, R., & Würtz, R. P.In Proceedings of IEEE International Workshops on Foundations and Applications of Self* Systems (pp. 132–137)@inproceedings{GriebenWürtz2017, author = {Grieben, Raul and Würtz, Rolf P.}, title = {Cue Integration by Similarity Rank List Coding — Application to Invariant Object Recognition}, booktitle = {Proceedings of IEEE International Workshops on Foundations and Applications of Self* Systems}, pages = {132–137}, year = {2017}, doi = {10.1109/FAS*W.2017.38}, }Grieben, R., & Würtz, R. P.. (2017). Cue Integration by Similarity Rank List Coding — Application to Invariant Object Recognition. In Proceedings of IEEE International Workshops on Foundations and Applications of Self* Systems (pp. 132–137). http://doi.org/10.1109/FAS*W.2017.38Texture attribute synthesis and transfer using feed-forward CNNs