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2012


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Towards a learning-theoretic analysis of spike-timing dependent plasticity

Balduzzi, D., Besserve, M.

In Advances in Neural Information Processing Systems 25, pages: 2465-2473, (Editors: P Bartlett and FCN Pereira and CJC. Burges and L Bottou and KQ Weinberger), Curran Associates Inc., 26th Annual Conference on Neural Information Processing Systems (NIPS), 2012 (inproceedings)

ei

PDF [BibTex]

2012


PDF [BibTex]


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Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database

Köhler, R., Hirsch, M., Mohler, B., Schölkopf, B., Harmeling, S.

In Computer Vision - ECCV 2012, LNCS Vol. 7578, pages: 27-40, (Editors: A. Fitzgibbon, S. Lazebnik, P. Perona, Y. Sato, and C. Schmid), Springer, Berlin, Germany, 12th European Conference on Computer Vision, ECCV , 2012 (inproceedings)

Abstract
Motion blur due to camera shake is one of the predominant sources of degradation in handheld photography. Single image blind deconvolution (BD) or motion deblurring aims at restoring a sharp latent image from the blurred recorded picture without knowing the camera motion that took place during the exposure. BD is a long-standing problem, but has attracted much attention recently, cumulating in several algorithms able to restore photos degraded by real camera motion in high quality. In this paper, we present a benchmark dataset for motion deblurring that allows quantitative performance evaluation and comparison of recent approaches featuring non-uniform blur models. To this end, we record and analyse real camera motion, which is played back on a robot platform such that we can record a sequence of sharp images sampling the six dimensional camera motion trajectory. The goal of deblurring is to recover one of these sharp images, and our dataset contains all information to assess how closely various algorithms approximate that goal. In a comprehensive comparison, we evaluate state-of-the-art single image BD algorithms incorporating uniform and non-uniform blur models.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Towards identifying and validating cognitive correlates in a passive Brain-Computer Interface for detecting Loss of Control

Zander, TO., Pape, AA.

In Proceedings of the 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, EMBC, 2012 (inproceedings)

ei

[BibTex]

[BibTex]


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Neural correlates of workload and puzzlement during loss of control

Pape, AA., Gerjets, P., Zander, TO.

In Meeting of the EARLI SIG 22 Neuroscience and Education, 2012 (inproceedings)

ei

[BibTex]

[BibTex]


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Hypothesis testing using pairwise distances and associated kernels

Sejdinovic, D., Gretton, A., Sriperumbudur, B., Fukumizu, K.

In Proceedings of the 29th International Conference on Machine Learning, pages: 1111-1118, (Editors: J Langford and J Pineau), Omnipress, New York, NY, USA, ICML, 2012 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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Efficient Training of Graph-Regularized Multitask SVMs

Widmer, C., Kloft, M., Görnitz, N., Rätsch, G.

In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML/PKDD 2012, LNCS Vol. 7523, pages: 633-647, (Editors: PA Flach and T De Bie and N Cristianini), Springer, Berlin, Germany, ECML, 2012 (inproceedings)

ei

DOI [BibTex]

DOI [BibTex]


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Hilbert Space Embeddings of POMDPs

Nishiyama, Y., Boularias, A., Gretton, A., Fukumizu, K.

In Conference on Uncertainty in Artificial Intelligence (UAI), 2012 (inproceedings)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Learning Throwing and Catching Skills

Kober, J., Mülling, K., Peters, J.

In IEEE/RSJ International Conference on Intelligent Robots and Systems , pages: 5167-5168, IROS, 2012 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Maximally Informative Interaction Learning for Scene Exploration

van Hoof, H., Kroemer, O., Ben Amor, H., Peters, J.

In IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 5152-5158, IROS, 2012 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Investigating the Neural Basis of Brain-Computer Interface (BCI)-based Stroke Rehabilitation

Meyer, T., Peters, J., Zander, T., Brötz, D., Soekadar, S., Schölkopf, B., Grosse-Wentrup, M.

In International Conference on NeuroRehabilitation (ICNR) , pages: 617-621, (Editors: JL Pons, D Torricelli, and M Pajaro), Springer, Berlin, Germany, ICNR, 2012 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function

Ortega, P., Grau-Moya, J., Genewein, T., Balduzzi, D., Braun, D.

In Advances in Neural Information Processing Systems 25, pages: 3014-3022, (Editors: P Bartlett and FCN Pereira and CJC. Burges and L Bottou and KQ Weinberger), Curran Associates Inc., 26th Annual Conference on Neural Information Processing Systems (NIPS), 2012 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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Algorithms for Learning Markov Field Policies

Boularias, A., Kroemer, O., Peters, J.

In Advances in Neural Information Processing Systems 25, pages: 2186-2194, (Editors: P Bartlett and FCN Pereira and CJC. Burges and L Bottou and KQ Weinberger), Curran Associates Inc., 26th Annual Conference on Neural Information Processing Systems (NIPS), 2012 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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Semi-Supervised Domain Adaptation with Copulas

Lopez-Paz, D., Hernandez-Lobato, J., Schölkopf, B.

In Advances in Neural Information Processing Systems 25, pages: 674-682, (Editors: P Bartlett, FCN Pereira, CJC. Burges, L Bottou, and KQ Weinberger), Curran Associates Inc., 26th Annual Conference on Neural Information Processing Systems (NIPS), 2012 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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Gradient Weights help Nonparametric Regressors

Kpotufe, S., Boularias, A.

In Advances in Neural Information Processing Systems 25, pages: 2870-2878, (Editors: P Bartlett and FCN Pereira and CJC. Burges and L Bottou and KQ Weinberger), 26th Annual Conference on Neural Information Processing Systems (NIPS), 2012 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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A Blind Deconvolution Approach for Pseudo CT Prediction from MR Image Pairs

Hirsch, M., Hofmann, M., Mantlik, F., Pichler, B., Schölkopf, B., Habeck, M.

In 19th IEEE International Conference on Image Processing (ICIP) , pages: 2953 -2956, IEEE, ICIP, 2012 (inproceedings)

ei

DOI [BibTex]

DOI [BibTex]


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A mixed model approach for joint genetic analysis of alternatively spliced transcript isoforms using RNA-Seq data

Rakitsch, B., Lippert, C., Topa, H., Borgwardt, KM., Honkela, A., Stegle, O.

In 2012 (inproceedings) Submitted

ei

Web [BibTex]

Web [BibTex]


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Evaluation of marginal likelihoods via the density of states

Habeck, M.

In Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012) , 22, pages: 486-494, (Editors: N Lawrence and M Girolami), JMLR: W&CP 22, AISTATS, 2012 (inproceedings)

Abstract
Bayesian model comparison involves the evaluation of the marginal likelihood, the expectation of the likelihood under the prior distribution. Typically, this high-dimensional integral over all model parameters is approximated using Markov chain Monte Carlo methods. Thermodynamic integration is a popular method to estimate the marginal likelihood by using samples from annealed posteriors. Here we show that there exists a robust and flexible alternative. The new method estimates the density of states, which counts the number of states associated with a particular value of the likelihood. If the density of states is known, computation of the marginal likelihood reduces to a one- dimensional integral. We outline a maximum likelihood procedure to estimate the density of states from annealed posterior samples. We apply our method to various likelihoods and show that it is superior to thermodynamic integration in that it is more flexible with regard to the annealing schedule and the family of bridging distributions. Finally, we discuss the relation of our method with Skilling's nested sampling.

ei

PDF [BibTex]

PDF [BibTex]


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Distributed multisensory signals acquisition and analysis in dyadic interactions

Tawari, A., Tran, C., Doshi, A., Zander, TO.

In Proceedings of the 2012 ACM Annual Conference on Human Factors in Computing Systems Extended Abstracts, pages: 2261-2266, (Editors: JA Konstan and EH Chi and K Höök), ACM, New York, NY, USA, CHI, 2012 (inproceedings)

ei

DOI [BibTex]

DOI [BibTex]


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Measuring Cognitive Load by means of EEG-data - how detailed is the picture we can get?

Scharinger, C., Cierniak, G., Walter, C., Zander, TO., Gerjets, P.

In Meeting of the EARLI SIG 22 Neuroscience and Education, 2012 (inproceedings)

ei

[BibTex]

[BibTex]


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Optimal kernel choice for large-scale two-sample tests

Gretton, A., Sriperumbudur, B., Sejdinovic, D., Strathmann, H., Balakrishnan, S., Pontil, M., Fukumizu, K.

In Advances in Neural Information Processing Systems 25, pages: 1214-1222, (Editors: P Bartlett and FCN Pereira and CJC. Burges and L Bottou and KQ Weinberger), Curran Associates Inc., 26th Annual Conference on Neural Information Processing Systems (NIPS), 2012 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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Topological optimization for continuum compliant mechanisms via morphological evolution of traditional mechanisms

Lum, GZ, Yeo, SH, Yang, GL, Teo, TJ, Sitti, M

In 4th International Conference on Computational Methods, pages: 8, 2012 (inproceedings)

pi

[BibTex]

[BibTex]


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Adaptive Coding of Actions and Observations

Ortega, PA, Braun, DA

pages: 1-4, NIPS Workshop on Information in Perception and Action, December 2012 (conference)

Abstract
The application of expected utility theory to construct adaptive agents is both computationally intractable and statistically questionable. To overcome these difficulties, agents need the ability to delay the choice of the optimal policy to a later stage when they have learned more about the environment. How should agents do this optimally? An information-theoretic answer to this question is given by the Bayesian control rule—the solution to the adaptive coding problem when there are not only observations but also actions. This paper reviews the central ideas behind the Bayesian control rule.

ei

link (url) [BibTex]

link (url) [BibTex]


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Free Energy and the Generalized Optimality Equations for Sequential Decision Making

Ortega, PA, Braun, DA

pages: 1-10, 10th European Workshop on Reinforcement Learning (EWRL), July 2012 (conference)

Abstract
The free energy functional has recently been proposed as a variational principle for bounded rational decision-making, since it instantiates a natural trade-off between utility gains and information processing costs that can be axiomatically derived. Here we apply the free energy principle to general decision trees that include both adversarial and stochastic environments. We derive generalized sequential optimality equations that not only include the Bellman optimality equations as a limit case, but also lead to well-known decision-rules such as Expectimax, Minimax and Expectiminimax. We show how these decision-rules can be derived from a single free energy principle that assigns a resource parameter to each node in the decision tree. These resource parameters express a concrete computational cost that can be measured as the amount of samples that are needed from the distribution that belongs to each node. The free energy principle therefore provides the normative basis for generalized optimality equations that account for both adversarial and stochastic environments.

ei

link (url) [BibTex]

link (url) [BibTex]


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Flapping Wings with DC-Motors via Direct, Elastic Transmissions

Azhar, M., Campolo, D., Lau, G., Sitti, M.

In Proceedings of International Conference on Intelligent Unmanned Systems, 8, 2012 (inproceedings)

pi

[BibTex]

[BibTex]


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Investigation of bioinspired gecko fibers to improve adhesion of HeartLander surgical robot

Tortora, G., Glass, P., Wood, N., Aksak, B., Menciassi, A., Sitti, M., Riviere, C.

In Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, pages: 908-911, 2012 (inproceedings)

pi

[BibTex]

[BibTex]


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Magnetic hysteresis for multi-state addressable magnetic microrobotic control

Diller, E., Miyashita, S., Sitti, M.

In Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, pages: 2325-2331, 2012 (inproceedings)

pi

[BibTex]

[BibTex]

2000


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Choosing nu in support vector regression with different noise models — theory and experiments

Chalimourda, A., Schölkopf, B., Smola, A.

In Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, IJCNN 2000, Neural Computing: New Challenges and Perspectives for the New Millennium, IEEE, International Joint Conference on Neural Networks, 2000 (inproceedings)

ei

[BibTex]

2000


[BibTex]


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Wing transmission for a micromechanical flying insect

Fearing, R. S., Chiang, K. H., Dickinson, M. H., Pick, D., Sitti, M., Yan, J.

In Robotics and Automation, 2000. Proceedings. ICRA’00. IEEE International Conference on, 2, pages: 1509-1516, 2000 (inproceedings)

pi

[BibTex]

[BibTex]

1998


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Prior knowledge in support vector kernels

Schölkopf, B., Simard, P., Smola, A., Vapnik, V.

In Advances in Neural Information Processing Systems 10, pages: 640-646 , (Editors: M Jordan and M Kearns and S Solla ), MIT Press, Cambridge, MA, USA, Eleventh Annual Conference on Neural Information Processing (NIPS), June 1998 (inproceedings)

ei

PDF Web [BibTex]

1998


PDF Web [BibTex]


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From regularization operators to support vector kernels

Smola, A., Schölkopf, B.

In Advances in Neural Information Processing Systems 10, pages: 343-349, (Editors: M Jordan and M Kearns and S Solla), MIT Press, Cambridge, MA, USA, 11th Annual Conference on Neural Information Processing (NIPS), June 1998 (inproceedings)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Nano tele-manipulation using virtual reality interface

Sitti, M., Horiguchi, S., Hashimoto, H.

In Industrial Electronics, 1998. Proceedings. ISIE’98. IEEE International Symposium on, 1, pages: 171-176, 1998 (inproceedings)

pi

[BibTex]

[BibTex]


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Tele-nanorobotics using atomic force microscope

Sitti, M., Hashimoto, H.

In Intelligent Robots and Systems, 1998. Proceedings., 1998 IEEE/RSJ International Conference on, 3, pages: 1739-1746, 1998 (inproceedings)

pi

[BibTex]

[BibTex]


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2D micro particle assembly using atomic force microscope

Sitti, M., Hirahara, K., Hashimoto, H.

In Micromechatronics and Human Science, 1998. MHS’98. Proceedings of the 1998 International Symposium on, pages: 143-148, 1998 (inproceedings)

pi

[BibTex]

[BibTex]


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Macro to nano tele-manipulation through nanoelectromechanical systems

Sitti, M., Hashimoto, H.

In Industrial Electronics Society, 1998. IECON’98. Proceedings of the 24th Annual Conference of the IEEE, 1, pages: 98-103, 1998 (inproceedings)

pi

[BibTex]

[BibTex]