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2014


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Single-Source Domain Adaptation with Target and Conditional Shift

Zhang, K., Schölkopf, B., Muandet, K., Wang, Z., Zhou, Z., Persello, C.

In Regularization, Optimization, Kernels, and Support Vector Machines, pages: 427-456, 19, Chapman & Hall/CRC Machine Learning & Pattern Recognition, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), Chapman and Hall/CRC, Boca Raton, USA, 2014 (inbook)

ei

[BibTex]

2014


[BibTex]


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Higher-Order Tensors in Diffusion Imaging

Schultz, T., Fuster, A., Ghosh, A., Deriche, R., Florack, L., Lim, L.

In Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data, pages: 129-161, Mathematics + Visualization, (Editors: Westin, C.-F., Vilanova, A. and Burgeth, B.), Springer, 2014 (inbook)

ei

[BibTex]

[BibTex]


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Fuzzy Fibers: Uncertainty in dMRI Tractography

Schultz, T., Vilanova, A., Brecheisen, R., Kindlmann, G.

In Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization, pages: 79-92, 8, Mathematics + Visualization, (Editors: Hansen, C. D., Chen, M., Johnson, C. R., Kaufman, A. E. and Hagen, H.), Springer, 2014 (inbook)

ei

[BibTex]

[BibTex]


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Nonconvex Proximal Splitting with Computational Errors

Sra, S.

In Regularization, Optimization, Kernels, and Support Vector Machines, pages: 83-102, 4, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), CRC Press, 2014 (inbook)

ei

[BibTex]

[BibTex]


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Addressing of Micro-robot Teams and Non-contact Micro-manipulation

Diller, E., Ye, Z., Giltinan, J., Sitti, M.

In Small-Scale Robotics. From Nano-to-Millimeter-Sized Robotic Systems and Applications, pages: 28-38, Springer Berlin Heidelberg, 2014 (incollection)

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Project Page [BibTex]

Project Page [BibTex]


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Robot Learning by Guided Self-Organization

Martius, G., Der, R., Herrmann, J. M.

In Guided Self-Organization: Inception, 9, pages: 223-260, Emergence, Complexity and Computation, Springer Berlin Heidelberg, 2014 (incollection)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Simulated Annealing

Gall, J.

In Encyclopedia of Computer Vision, pages: 737-741, 0, (Editors: Ikeuchi, K. ), Springer Verlag, 2014, to appear (inbook)

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[BibTex]

[BibTex]

2012


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Expectation-Maximization methods for solving (PO)MDPs and optimal control problems

Toussaint, M., Storkey, A., Harmeling, S.

In Inference and Learning in Dynamic Models, (Editors: Barber, D., Cemgil, A.T. and Chiappa, S.), Cambridge University Press, Cambridge, UK, January 2012 (inbook) In press

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PDF [BibTex]

2012


PDF [BibTex]


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Inferential structure determination from NMR data

Habeck, M.

In Bayesian methods in structural bioinformatics, pages: 287-312, (Editors: Hamelryck, T., Mardia, K. V. and Ferkinghoff-Borg, J.), Springer, New York, 2012 (inbook)

ei

[BibTex]

[BibTex]


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Robot Learning

Sigaud, O., Peters, J.

In Encyclopedia of the sciences of learning, (Editors: Seel, N.M.), Springer, Berlin, Germany, 2012 (inbook)

ei

Web [BibTex]

Web [BibTex]


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Reinforcement Learning in Robotics: A Survey

Kober, J., Peters, J.

In Reinforcement Learning, 12, pages: 579-610, (Editors: Wiering, M. and Otterlo, M.), Springer, Berlin, Germany, 2012 (inbook)

Abstract
As most action generation problems of autonomous robots can be phrased in terms of sequential decision problems, robotics offers a tremendously important and interesting application platform for reinforcement learning. Similarly, the real-world challenges of this domain pose a major real-world check for reinforcement learning. Hence, the interplay between both disciplines can be seen as promising as the one between physics and mathematics. Nevertheless, only a fraction of the scientists working on reinforcement learning are sufficiently tied to robotics to oversee most problems encountered in this context. Thus, we will bring the most important challenges faced by robot reinforcement learning to their attention. To achieve this goal, we will attempt to survey most work that has successfully applied reinforcement learning to behavior generation for real robots. We discuss how the presented successful approaches have been made tractable despite the complexity of the domain and will study how representations or the inclusion of prior knowledge can make a significant difference. As a result, a particular focus of our chapter lies on the choice between model-based and model-free as well as between value function-based and policy search methods. As a result, we obtain a fairly complete survey of robot reinforcement learning which should allow a general reinforcement learning researcher to understand this domain.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Higher-Order Tensors in Diffusion MRI

Schultz, T., Fuster, A., Ghosh, A., Deriche, R., Florack, L., Lim, L.

In Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data, (Editors: Westin, C. F., Vilanova, A. and Burgeth, B.), Springer, 2012 (inbook) Accepted

ei

[BibTex]

[BibTex]


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Automated Tip-Based 2-D Mechanical Assembly of Micro/Nanoparticles

Onal, C. D., Ozcan, O., Sitti, M.

In Feedback Control of MEMS to Atoms, pages: 69-108, Springer US, 2012 (incollection)

pi

[BibTex]

[BibTex]


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The principles of XMCD and its application to L-edges in transition metals

Schütz, G.

In Linear and Chiral Dichroism in the Electron Miroscope, pages: 23-42, Pan Stanford Publishing Pte.Ltd., Singapore, 2012 (incollection)

mms

[BibTex]

[BibTex]


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An Introduction to Random Forests for Multi-class Object Detection

Gall, J., Razavi, N., van Gool, L.

In Outdoor and Large-Scale Real-World Scene Analysis, 7474, pages: 243-263, LNCS, (Editors: Dellaert, Frank and Frahm, Jan-Michael and Pollefeys, Marc and Rosenhahn, Bodo and Leal-Taix’e, Laura), Springer, 2012 (incollection)

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code code for Hough forest publisher's site pdf Project Page [BibTex]

code code for Hough forest publisher's site pdf Project Page [BibTex]


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Home 3D body scans from noisy image and range data

Weiss, A., Hirshberg, D., Black, M. J.

In Consumer Depth Cameras for Computer Vision: Research Topics and Applications, pages: 99-118, 6, (Editors: Andrea Fossati and Juergen Gall and Helmut Grabner and Xiaofeng Ren and Kurt Konolige), Springer-Verlag, 2012 (incollection)

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Project Page [BibTex]

Project Page [BibTex]


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Structural and chemical characterization on the nanoscale

Stierle, A., Carstanjen, H.-D., Hofmann, S.

In Nanoelectronics and Information Technology. Advanced Electronic Materials and Novel Devices, pages: 233-254, Wiley-VCH, Weinheim, 2012 (incollection)

mms

[BibTex]

[BibTex]


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Rutherford Backscattering

Carstanjen, H. D.

In Nanoelectronics and Information Technology. Advanced Electronic Materials and Novel Devices, pages: 250-252, WILEY-VCH Verlag, Weinheim, Germany, 2012 (incollection)

mms

[BibTex]

[BibTex]