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2014


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Bayesian Gait Optimization for Bipedal Locomotion

Calandra, R., Gopalan, N., Seyfarth, A., Peters, J., Deisenroth, M.

In Proceedings of the 8th International Conference on Learning and Intelligent Optimization , LNCS 8426, pages: 274-290, Lecture Notes in Computer Science, (Editors: Pardalos, PM., Resende, MGC., Vogiatzis, C., and Walteros, JL.), Springer, LION, 2014 (inproceedings)

ei

PDF DOI [BibTex]

2014


PDF DOI [BibTex]


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Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot

Lioutikov, R., Kroemer, O., Peters, J., Maeda, G.

In Proceedings of the 13th International Conference on Intelligent Autonomous Systems, 302, pages: 1601-1611, Advances in Intelligent Systems and Computing, (Editors: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H.), Springer, IAS, 2014 (inproceedings)

ei

DOI [BibTex]

DOI [BibTex]


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Impact of Large-Scale Climate Extremes on Biospheric Carbon Fluxes: An Intercomparison Based on MsTMIP Data

Zscheischler, J., Michalak, A., Schwalm, M., Mahecha, M., Huntzinger, D., Reichstein, M., Berthier, G., Ciais, P., Cook, R., El-Masri, B., Huang, M., Ito, A., Jain, A., King, A., Lei, H., Lu, C., Mao, J., Peng, S., Poulter, B., Ricciuto, D., Shi, X., Tao, B., Tian, H., Viovy, N., Wang, W., Wei, Y., Yang, J., Zeng, N.

Global Biogeochemical Cycles, 2014 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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A Brain-Computer Interface Based on Self-Regulation of Gamma-Oscillations in the Superior Parietal Cortex

Grosse-Wentrup, M., Schölkopf, B.

Journal of Neural Engineering, 11(5):056015, 2014 (article)

Abstract
Objective. Brain–computer interface (BCI) systems are often based on motor- and/or sensory processes that are known to be impaired in late stages of amyotrophic lateral sclerosis (ALS). We propose a novel BCI designed for patients in late stages of ALS that only requires high-level cognitive processes to transmit information from the user to the BCI. Approach. We trained subjects via EEG-based neurofeedback to self-regulate the amplitude of gamma-oscillations in the superior parietal cortex (SPC). We argue that parietal gamma-oscillations are likely to be associated with high-level attentional processes, thereby providing a communication channel that does not rely on the integrity of sensory- and/or motor-pathways impaired in late stages of ALS. Main results. Healthy subjects quickly learned to self-regulate gamma-power in the SPC by alternating between states of focused attention and relaxed wakefulness, resulting in an average decoding accuracy of 70.2%. One locked-in ALS patient (ALS-FRS-R score of zero) achieved an average decoding accuracy significantly above chance-level though insufficient for communication (55.8%). Significance. Self-regulation of gamma-power in the SPC is a feasible paradigm for brain–computer interfacing and may be preserved in late stages of ALS. This provides a novel approach to testing whether completely locked-in ALS patients retain the capacity for goal-directed thinking.

ei

Web DOI [BibTex]


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Kernel Mean Estimation via Spectral Filtering

Muandet, K., Sriperumbudur, B., Schölkopf, B.

In Advances in Neural Information Processing Systems 27, pages: 1-9, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

ei

Web link (url) [BibTex]

Web link (url) [BibTex]


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Consistency of Causal Inference under the Additive Noise Model

Kpotufe, S., Sgouritsa, E., Janzing, D., Schölkopf, B.

In Proceedings of the 31st International Conference on Machine Learning, W&CP 32 (1), pages: 478-495, (Editors: Eric P. Xing and Tony Jebara), JMLR, ICML, 2014 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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On power law distributions in large-scale taxonomies

Babbar, R., Metzig, C., Partalas, I., Gaussier, E., Amini, M.

SIGKDD Explorations, Special Issue on Big Data, 16(1):47-56, 2014 (article)

ei

[BibTex]

[BibTex]


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Quantifying statistical dependency

Besserve, M.

Research Network on Learning Systems Summer School, 2014 (talk)

ei

[BibTex]

[BibTex]


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Predicting Motor Learning Performance from Electroencephalographic Data

Meyer, T., Peters, J., Zander, T., Schölkopf, B., Grosse-Wentrup, M.

Journal of NeuroEngineering and Rehabilitation, 11:24, 2014 (article)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Active Learning of Linear Embeddings for Gaussian Processes

Garnett, R., Osborne, M., Hennig, P.

In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, pages: 230-239, (Editors: NL Zhang and J Tian), AUAI Press , Corvallis, Oregon, UAI2014, 2014, another link: http://arxiv.org/abs/1310.6740 (inproceedings)

ei pn

PDF Web [BibTex]

PDF Web [BibTex]


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Special issue on autonomous grasping and manipulation

Ben Amor, H., Saxena, A., Hudson, N., Peters, J.

Autonomous Robots, 36(1-2):1-3, 2014 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Evaluation of Positron Emission Tomographic Tracers for Imaging of Papillomavirus-Induced Tumors in Rabbits

Probst, S., Wiehr, S., Mantlik, F., Schmidt, H., Kolb, A., Münch, P., Delcuratolo, M., Stubenrauch, F., Pichler, B., Iftner, T.

Molecular Imaging, 13(1):1536-0121, 2014 (article)

ei

Web [BibTex]

Web [BibTex]


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Decoding Index Finger Position from EEG Using Random Forests

Weichwald, S., Meyer, T., Schölkopf, B., Ball, T., Grosse-Wentrup, M.

In 4th International Workshop on Cognitive Information Processing (CIP), IEEE, CIP, 2014 (inproceedings)

ei

PDF Arxiv DOI [BibTex]

PDF Arxiv DOI [BibTex]


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An Experimental Comparison of Bayesian Optimization for Bipedal Locomotion

Calandra, R., Seyfarth, A., Peters, J., Deisenroth, M.

In Proceedings of 2014 IEEE International Conference on Robotics and Automation, pages: 1951-1958, IEEE, ICRA, 2014 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Multi-Task Policy Search for Robotics

Deisenroth, M., Englert, P., Peters, J., Fox, D.

In Proceedings of 2014 IEEE International Conference on Robotics and Automation, pages: 3876-3881, IEEE, ICRA, 2014 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Sample-Based Information-Theoretic Stochastic Optimal Control

Lioutikov, R., Paraschos, A., Peters, J., Neumann, G.

In Proceedings of 2014 IEEE International Conference on Robotics and Automation, pages: 3896-3902, IEEE, ICRA, 2014 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Extreme events in gross primary production: a characterization across continents

Zscheischler, J., Reichstein, M., Harmeling, S., Rammig, A., Tomelleri, E., Mahecha, M.

Biogeosciences, 11, pages: 2909-2924, 2014 (article)

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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FID-guided retrospective motion correction based on autofocusing

Babayeva, M., Loktyushin, A., Kober, T., Granziera, C., Nickisch, H., Gruetter, R., Krueger, G.

Joint Annual Meeting ISMRM-ESMRMB, Milano, Italy, 2014 (poster)

ei

[BibTex]

[BibTex]


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Probabilistic Shortest Path Tractography in DTI Using Gaussian Process ODE Solvers

Schober, M., Kasenburg, N., Feragen, A., Hennig, P., Hauberg, S.

In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, Lecture Notes in Computer Science Vol. 8675, pages: 265-272, (Editors: P. Golland, N. Hata, C. Barillot, J. Hornegger and R. Howe), Springer, Heidelberg, MICCAI, 2014 (inproceedings)

ei pn

DOI [BibTex]

DOI [BibTex]


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Estimating Causal Effects by Bounding Confounding

Geiger, P., Janzing, D., Schölkopf, B.

In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence , pages: 240-249 , (Editors: Nevin L. Zhang and Jin Tian), AUAI Press Corvallis, Oregon , UAI, 2014 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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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]

[BibTex]


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Re-ranking Approach to Classification in Large-scale Power-law Distributed Category Systems

Babbar, R., Partalas, I., Gaussier, E., Amini, M.

In Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval, pages: 1059-1062, (Editors: S Geva and A Trotman and P Bruza and CLA Clarke and K Järvelin), ACM, New York, NY, USA, SIGIR, 2014 (inproceedings)

ei

DOI [BibTex]

DOI [BibTex]


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Kernel Mean Estimation and Stein Effect

Muandet, K., Fukumizu, K., Sriperumbudur, B., Gretton, A., Schölkopf, B.

In Proceedings of the 31st International Conference on Machine Learning, W&CP 32 (1), pages: 10-18, (Editors: Eric P. Xing and Tony Jebara), JMLR, ICML, 2014 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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Indirect Robot Model Learning for Tracking Control

Bocsi, B., Csató, L., Peters, J.

Advanced Robotics, 28(9):589-599, 2014 (article)

ei

PDF DOI [BibTex]


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An extended approach for spatiotemporal gapfilling: dealing with large and systematic gaps in geoscientific datasets

v Buttlar, J., Zscheischler, J., Mahecha, M.

Nonlinear Processes in Geophysics, 21(1):203-215, 2014 (article)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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On the Quantification Accuracy, Homogeneity, and Stability of Simultaneous Positron Emission Tomography/Magnetic Resonance Imaging Systems

Schmidt, H., Schwenzer, N., Bezrukov, I., Mantlik, F., Kolb, A., Kupferschläger, J., Pichler, B.

Investigative Radiology, 49(6):373-381, 2014 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Active Reward Learning

Daniel, C., Viering, M., Metz, J., Kroemer, O., Peters, J.

In Proceedings of Robotics: Science & Systems, (Editors: Fox, D., Kavraki, LE., and Kurniawati, H.), RSS, 2014 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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Multi-modal filtering for non-linear estimation

Kamthe, S., Peters, J., Deisenroth, M.

In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, pages: 7979-7983, IEEE, ICASSP, 2014 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Natural Evolution Strategies

Wierstra, D., Schaul, T., Glasmachers, T., Sun, Y., Peters, J., Schmidhuber, J.

Journal of Machine Learning Research, 15, pages: 949-980, 2014 (article)

ei

PDF [BibTex]

PDF [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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Factors controlling decomposition rates of fine root litter in temperate forests and grasslands

Solly, E., Schöning, I., Boch, S., Kandeler, E., Marhan, S., Michalzik, B., Müller, J., Zscheischler, J., Trumbore, S., Schrumpf, M.

Plant and Soil, 2014 (article)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Inferring latent structures via information inequalities

Chaves, R., Luft, L., Maciel, T., Gross, D., Janzing, D., Schölkopf, B.

In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, pages: 112-121, (Editors: NL Zhang and J Tian), AUAI Press, Corvallis, Oregon, UAI, 2014 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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Causal Discovery with Continuous Additive Noise Models

Peters, J., Mooij, J., Janzing, D., Schölkopf, B.

Journal of Machine Learning Research, 15, pages: 2009-2053, 2014 (article)

ei

PDF Web [BibTex]

PDF Web [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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Cluster analysis of sharp-wave ripple field potential signatures in the macaque hippocampus

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M.

Computational and Systems Neuroscience Meeting (COSYNE), 2014 (poster)

ei

[BibTex]

[BibTex]


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A few extreme events dominate global interannual variability in gross primary production

Zscheischler, J., Mahecha, M., v Buttlar, J., Harmeling, S., Jung, M., Rammig, A., Randerson, J., Schölkopf, B., Seneviratne, S., Tomelleri, E., Zaehle, S., Reichstein, M.

Environmental Research Letters, 9(3):035001, 2014 (article)

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Policy Search For Learning Robot Control Using Sparse Data

Bischoff, B., Nguyen-Tuong, D., van Hoof, H., McHutchon, A., Rasmussen, C., Knoll, A., Peters, J., Deisenroth, M.

In Proceedings of 2014 IEEE International Conference on Robotics and Automation, pages: 3882-3887, IEEE, ICRA, 2014 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Learning to Unscrew a Light Bulb from Demonstrations

Manschitz, S., Kober, J., Gienger, M., Peters, J.

In Proceedings for the joint conference of ISR 2014, 45th International Symposium on Robotics and Robotik 2014, 2014 (inproceedings)

ei

[BibTex]

[BibTex]


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Towards Neurofeedback Training of Associative Brain Areas for Stroke Rehabilitation

Özdenizci, O., Meyer, T., Cetin, M., Grosse-Wentrup, M.

In Proceedings of the 6th International Brain-Computer Interface Conference, (Editors: G Müller-Putz and G Bauernfeind and C Brunner and D Steyrl and S Wriessnegger and R Scherer), 2014 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Kernel methods in system identification, machine learning and function estimation: A survey

Pillonetto, G., Dinuzzo, F., Chen, T., De Nicolao, G., Ljung, L.

Automatica, 50(3):657-682, 2014 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Development of a novel depth of interaction PET detector using highly multiplexed G-APD cross-strip encoding

Kolb, A., Parl, C., Mantlik, F., Liu, C., Lorenz, E., Renker, D., Pichler, B.

Medical Physics, 41(8), 2014 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature

Gunter, T., Osborne, M., Garnett, R., Hennig, P., Roberts, S.

In Advances in Neural Information Processing Systems 27, pages: 2789-2797, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

ei pn

Web link (url) [BibTex]

Web link (url) [BibTex]


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Circular polarization interferometry: circularly polarized modes of cholesteric liquid crystals

Sanchez-Castillo, A., Eslami, S., Giesselmann, F., Fischer, P.

OPTICS EXPRESS, 22(25):31227-31236, 2014 (article)

Abstract
We describe a novel polarization interferometer which permits the determination of the refractive indices for circularly-polarized light. It is based on a Jamin-Lebedeff interferometer, modified with waveplates, and permits us to experimentally determine the refractive indices n(L) and n(R) of the respectively left- and right-circularly polarized modes in a cholesteric liquid crystal. Whereas optical rotation measurements only determine the circular birefringence, i.e. the difference (n(L) - n(R)), the interferometer also permits the determination of their absolute values. We report refractive indices of a cholesteric liquid crystal in the region of selective (Bragg) reflection as a function of temperature. (C) 2014 Optical Society of America

pf

DOI [BibTex]

DOI [BibTex]


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Self-Propelling Nanomotors in the Presence of Strong Brownian Forces

Lee, T., Alarcon-Correa, M., Miksch, C., Hahn, K., Gibbs, J. G., Fischer, P.

NANO LETTERS, 14(5):2407-2412, 2014 (article)

Abstract
Motility in living systems is due to an array of complex molecular nanomotors that are essential for the function and survival of cells. These protein nanomotors operate not only despite of but also because of stochastic forces. Artificial means of realizing motility rely on local concentration or temperature gradients that are established across a particle, resulting in slip velocities at the particle surface and thus motion of the particle relative to the fluid. However, it remains unclear if these artificial motors can function at the smallest of scales, where Brownian motion dominates and no actively propelled living organisms can be found. Recently, the first reports have appeared suggesting that the swimming mechanisms of artificial structures may also apply to enzymes that are catalytically active. Here we report a scheme to realize artificial Janus nanoparticles (JNPs) with an overall size that is comparable to that of some enzymes similar to 30 nm. Our JNPs can catalyze the decomposition of hydrogen peroxide to water and oxygen and thus actively move by self-electrophoresis. Geometric anisotropy of the Pt-Au Janus nanoparticles permits the simultaneous observation of their translational and rotational motion by dynamic light scattering. While their dynamics is strongly influenced by Brownian rotation, the artificial Janus nanomotors show bursts of linear ballistic motion resulting in enhanced diffusion.

pf

DOI [BibTex]


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A global analysis of extreme events and consequences for the terrestrial carbon cycle

Zscheischler, J.

Diss. No. 22043, ETH Zurich, Switzerland, ETH Zurich, Switzerland, 2014 (phdthesis)

ei

[BibTex]

[BibTex]


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A Self-Tuning LQR Approach Demonstrated on an Inverted Pendulum

Trimpe, S., Millane, A., Doessegger, S., D’Andrea, R.

In Proceedings of the 19th IFAC World Congress, Cape Town, South Africa, 2014 (inproceedings)

am ics

PDF Supplementary material DOI [BibTex]

PDF Supplementary material DOI [BibTex]


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Epidural electrocorticography for monitoring of arousal in locked-in state

Martens, S., Bensch, M., Halder, S., Hill, J., Nijboer, F., Ramos-Murguialday, A., Schölkopf, B., Birbaumer, N., Gharabaghi, A.

Frontiers in Human Neuroscience, 8(861), 2014 (article)

ei

DOI [BibTex]

DOI [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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Fast Newton methods for the group fused lasso

Wytock, M., Sra, S., Kolter, J. Z.

In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, pages: 888-897, (Editors: Zhang, N. L. and Tian, J.), AUAI Press, UAI, 2014 (inproceedings)

ei

link (url) [BibTex]

link (url) [BibTex]