2333 results (BibTeX)

2017


Approximate Steepest Coordinate Descent

Stich, S., Raj, A., Jaggi, M.

Proceedings of the 34th International Conference on Machine Learning (ICML 2017), 2017 (conference) Accepted

[BibTex]

2017

[BibTex]


Local Group Invariant Representations via Orbit Embeddings

Raj, A., Kumar, A., Mroueh, Y., Fletcher, T., Schölkopf, B.

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), 54, pages: 1225-1235, Proceedings of Machine Learning Research, (Editors: Aarti Singh and Jerry Zhu), 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


Local Bayesian Optimization of Motor Skills

Akrour, R., Sorokin, D., Peters, J., Neumann, G.

Proceedings of the 34th International Conference on Machine Learning (ICML 2017), 2017 (conference) Accepted

[BibTex]

[BibTex]


Pre-Movement Contralateral EEG Low Beta Power Is Modulated with Motor Adaptation Learning

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference (GBCIC 2017), 2017 (conference) Accepted

[BibTex]

[BibTex]


Correlations of Motor Adaptation Learning and Modulation of Resting-State Sensorimotor EEG Activity

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference (GBCIC 2017), 2017 (conference) Accepted

[BibTex]

[BibTex]


Investigating Music Imagery as a Cognitive Paradigm for Low-Cost Brain-Computer Interfaces

Grossberger, L., Hohmann, M., Peters, J., M., G.

Proceedings of the 7th Graz Brain-Computer Interface Conference (GBCIC 2017), 2017 (conference) Accepted

[BibTex]

[BibTex]


Bayesian Regression for Artifact Correction in Electroencephalography

Fiebig, K., Jayaram, V., Hesse, T., Blank, A., Peters, J., M., G.

Proceedings of the 7th Graz Brain-Computer Interface Conference (GBCIC 2017), 2017 (conference) Accepted

[BibTex]

[BibTex]


Closing One’s Eyes Affects Amplitude Modulation but Not Frequency Modulation in a Cognitive BCI

Görner, M., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference (GBCIC 2017) , 2017 (conference) Accepted

[BibTex]

[BibTex]


A Guided Task for Cognitive Brain-Computer Interfaces

Moser, J., Hohmann, M., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference (GBCIC 2017), 2017 (conference) Accepted

[BibTex]

[BibTex]


Electroencephalographic identifiers of motor adaptation learning

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

Journal of Neural Engineering, 2017 (article) Submitted

[BibTex]

[BibTex]


Weakly-Supervised Localization of Diabetic Retinopathy Lesions in Retinal Fundus Images

Gondal, W., Köhler, J., Grzeszick, R., Fink, G., Hirsch, M.

IEEE International Conference on Image Processing (ICIP 207), 2017 (conference) Accepted

[BibTex]

[BibTex]


Dynamic Time-of-Flight

Schober, M., Adam, A., Yair, O., Mazor, S., Nowozin, S.

The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 (conference) Accepted

[BibTex]

[BibTex]


Discovering Causal Signals in Images

Lopez-Paz, D., Nishihara, R., Chintala, S., Schölkopf, B., Bottou, L.

The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 (conference) Accepted

[BibTex]

[BibTex]


Flexible Spatio-Temporal Networks for Video Prediction

Lu, C., Hirsch, M., Schölkopf, B.

The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 (conference) Accepted

[BibTex]

[BibTex]


Frequency Peak Features for Low-Channel Classification in Motor Imagery Paradigms

Jayaram, V., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the 8th International IEEE EMBS Conference on Neural Engineering (NER 2017), 2017 (conference) Accepted

[BibTex]

[BibTex]


AdaGAN: Boosting Generative Models

Tolstikhin, I., Gelly, S., Bousquet, O., Simon-Gabriel, C., Schölkopf, B.

2017 (techreport) Submitted

Arxiv [BibTex]

Arxiv [BibTex]


DeepCoder: Learning to Write Programs

Balog, M., Gaunt, A., Brockschmidt, M., Nowozin, S., Tarlow, D.

5th International Conference on Learning Representations (ICLR), 2017 (conference) Accepted

Arxiv [BibTex]

Arxiv [BibTex]


Multi-frame blind image deconvolution through split frequency - phase recovery

Gauci, A., Abela, J., Cachia, E., Hirsch, M., ZarbAdami, K.

Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), pages: 1022511, (Editors: Yulin Wang, Tuan D. Pham, Vit Vozenilek, David Zhang, Yi Xie), 2017 (conference)

DOI [BibTex]

DOI [BibTex]


Thumb md reliability icon
Distilling Information Reliability and Source Trustworthiness from Digital Traces

Tabibian, B., Valera, I., Farajtabar, M., Song, L., Schölkopf, B., Gomez Rodriguez, M.

Proceedings of the 26th International Conference on World Wide Web (WWW2017), 2017 (conference) Accepted

Project [BibTex]

Project [BibTex]


DiSMEC – Distributed Sparse Machines for Extreme Multi-label Classification

Babbar, R., Schölkopf, B.

Proceedings of the Tenth ACM International Conference on Web Search and Data Mining (WSDM 2017), pages: 721-729, 2017 (conference)

DOI [BibTex]

DOI [BibTex]


BundleMAP: Anatomically Localized Classification, Regression, and Hypothesis Testing in Diffusion MRI

Khatami, M., Schmidt-Wilcke, T., Sundgren, P., Abbasloo, A., Schölkopf, B., Schultz, T.

Pattern Recognition, 63, pages: 593-600, 2017 (article)

DOI [BibTex]

DOI [BibTex]


End-to-End Learning for Image Burst Deblurring

Wieschollek, P., Schölkopf, B., Lensch, H., Hirsch, M.

Computer Vision - ACCV 2016 - 13th Asian Conference on Computer Vision, 10114, pages: 35-51, Image Processing, Computer Vision, Pattern Recognition, and Graphics, (Editors: Lai, S.-H., Lepetit, V., Nishino, K., and Sato, Y. ), Springer, 2017 (conference)

[BibTex]

[BibTex]


Unsupervised clustering of EOG as a viable substitute for optical eye-tracking

Flad, N., Fomina, T., Bülthoff, H., Chuang, L.

In First Workshop on Eye Tracking and Visualization (ETVIS 2015), pages: 151-167, Mathematics and Visualization, (Editors: Burch, M., Chuang, L., Fisher, B., Schmidt, A., and Weiskopf, D.), Springer, 2017 (inbook)

DOI [BibTex]

DOI [BibTex]


Model Selection for Gaussian Mixture Models

Huang, T., Peng, H., Zhang, K.

Statistica Sinica, 27(1):147-169, 2017 (article)

link (url) [BibTex]

link (url) [BibTex]


Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills

Kupcsik, A., Deisenroth, M., Peters, J., Ai Poh, L., Vadakkepat, V., Neumann, G.

Artificial Intelligence, 247, pages: 415-439, 2017, Special Issue on AI and Robotics (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Anticipatory Action Selection for Human-Robot Table Tennis

Wang, Z., Boularias, A., Mülling, K., Schölkopf, B., Peters, J.

Artificial Intelligence, 247, pages: 399-414, 2017, Special Issue on AI and Robotics (article)

Abstract
Abstract Anticipation can enhance the capability of a robot in its interaction with humans, where the robot predicts the humans' intention for selecting its own action. We present a novel framework of anticipatory action selection for human-robot interaction, which is capable to handle nonlinear and stochastic human behaviors such as table tennis strokes and allows the robot to choose the optimal action based on prediction of the human partner's intention with uncertainty. The presented framework is generic and can be used in many human-robot interaction scenarios, for example, in navigation and human-robot co-manipulation. In this article, we conduct a case study on human-robot table tennis. Due to the limited amount of time for executing hitting movements, a robot usually needs to initiate its hitting movement before the opponent hits the ball, which requires the robot to be anticipatory based on visual observation of the opponent's movement. Previous work on Intention-Driven Dynamics Models (IDDM) allowed the robot to predict the intended target of the opponent. In this article, we address the problem of action selection and optimal timing for initiating a chosen action by formulating the anticipatory action selection as a Partially Observable Markov Decision Process (POMDP), where the transition and observation are modeled by the \{IDDM\} framework. We present two approaches to anticipatory action selection based on the \{POMDP\} formulation, i.e., a model-free policy learning method based on Least-Squares Policy Iteration (LSPI) that employs the \{IDDM\} for belief updates, and a model-based Monte-Carlo Planning (MCP) method, which benefits from the transition and observation model by the IDDM. Experimental results using real data in a simulated environment show the importance of anticipatory action selection, and that \{POMDPs\} are suitable to formulate the anticipatory action selection problem by taking into account the uncertainties in prediction. We also show that existing algorithms for POMDPs, such as \{LSPI\} and MCP, can be applied to substantially improve the robot's performance in its interaction with humans.

DOI [BibTex]

DOI [BibTex]

2016


Unsupervised Domain Adaptation in the Wild : Dealing with Asymmetric Label Set

Mittal, A., Raj, A., Namboodiri, V., Tuytelaars, T.

2016 (misc)

Arxiv [BibTex]

2016


Screening Rules for Convex Problems

Raj, A., Olbrich, J., Gärtner, B., Schölkopf, B., Jaggi, M.

2016 (article) Submitted

[BibTex]

[BibTex]


PGO wave-triggered functional MRI: mapping the networks underlying synaptic consolidation

Logothetis, N., Murayama, Y., Ramirez-Villegas, J., Besserve, M., Evrard, H.

47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)

[BibTex]

[BibTex]


Hippocampal neural events predict ongoing brain-wide BOLD activity

Besserve, M., Logothetis, N.

47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)

[BibTex]

[BibTex]


Statistical source separation of rhythmic LFP patterns during sharp wave ripples in the macaque hippocampus

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

47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)

[BibTex]

[BibTex]


Multiparametric Imaging of Ischemic Stroke using [89Zr]-Desferal-EPO-PET/MRI in combination with Gaussian Mixture Modeling enables unsupervised lesions identification

Castaneda, S., Katiyar, P., Russo, F., Maurer, A., Patzwaldt, K., Poli, S., Calaminus, C., Disselhorst, J., Ziemann, U., Pichler, B.

European Molecular Imaging Meeting, 2016 (poster)

link (url) [BibTex]

link (url) [BibTex]


Analysis of multiparametric MRI using a semi-supervised random forest framework allows the detection of therapy response in ischemic stroke

Castaneda, S., Katiyar, P., Russo, F., Calaminus, C., Disselhorst, J., Ziemann, U., Kohlhofer, U., Quintanilla-Martinez, L., Poli, S., Pichler, B.

World Molecular Imaging Conference, 2016 (talk)

link (url) [BibTex]

link (url) [BibTex]


Novel Random Forest based framework enables the segmentation of cerebral ischemic regions using multiparametric MRI

Katiyar, P., Castaneda, S., Patzwaldt, K., Russo, F., Poli, S., Ziemann, U., Disselhorst, J., Pichler, B.

European Molecular Imaging Meeting, 2016 (poster)

link (url) [BibTex]

link (url) [BibTex]


Multi-view learning on multiparametric PET/MRI quantifies intratumoral heterogeneity and determines therapy efficacy

Katiyar, P., Divine, M., Kohlhofer, U., Quintanilla-Martinez, L., Siegemund, M., Pfizenmaier, K., Kontermann, R., Pichler, B., Disselhorst, J.

World Molecular Imaging Conference, 2016 (talk)

link (url) [BibTex]

link (url) [BibTex]


Spectral Clustering predicts tumor tissue heterogeneity using dynamic 18F-FDG PET: a complement to the standard compartmental modeling approach

Katiyar, P., Divine, M., Kohlhofer, U., Quintanilla-Martinez, L., Schölkopf, B., Pichler, B., Disselhorst, J.

Journal of Nuclear Medicine, 2016, (published ahead of print November 3, 2016) (article)

DOI [BibTex]

DOI [BibTex]


A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological Validation

Katiyar, P., Divine, M., Kohlhofer, U., Quintanilla-Martinez, L., Schölkopf, B., Disselhorst, J.

Molecular Imaging and Biology, pages: 1-7, 2016 (article)

DOI [BibTex]

DOI [BibTex]


Experimental and causal view on information integration in autonomous agents

Geiger, P., Hofmann, K., Schölkopf, B.

Proceedings of the 6th International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2016), pages: 21-28, (Editors: Hatzilygeroudis, I. and Palade, V.), 2016 (conference)

link (url) [BibTex]

link (url) [BibTex]


The Mondrian Kernel

Balog, M., Lakshminarayanan, B., Ghahramani, Z., Roy, D., Teh, Y.

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence (UAI), (Editors: Ihler, Alexander T. and Janzing, Dominik), 2016 (conference)

Arxiv link (url) [BibTex]

Arxiv link (url) [BibTex]


Learning High-Order Filters for Efficient Blind Deconvolution of Document Photographs

Xiao, L., Wang, J., Heidrich, W., Hirsch, M.

Computer Vision - ECCV 2016, Lecture Notes in Computer Science, LNCS 9907, Part III, pages: 734-749, (Editors: Bastian Leibe, Jiri Matas, Nicu Sebe and Max Welling), Springer, 2016 (conference)

DOI [BibTex]

DOI [BibTex]


easyGWAS: A Cloud-based Platform for Comparing the Results of Genome-wide Association Studies

Grimm, D., Roqueiro, D., Salome, P., Kleeberger, S., Greshake, B., Zhu, W., Liu, C., Lippert, C., Stegle, O., Schölkopf, B., Weigel, D., Borgwardt, K.

The Plant Cell, 2016 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS

Fomina, T., Lohmann, G., Erb, M., Ethofer, T., Schölkopf, B., Grosse-Wentrup, M.

Journal of Neural Engineering, 13(6):066021, 2016 (article)

link (url) [BibTex]

link (url) [BibTex]


Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels

Tolstikhin, I., Sriperumbudur, B., Schölkopf, B.

Advances in Neural Information Processing Systems 29, pages: 1930-1938, (Editors: D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett), Curran Associates, Inc., 30th Annual Conference on Neural Information Processing Systems (NIPS), 2016 (conference)

link (url) [BibTex]

link (url) [BibTex]


Consistent Kernel Mean Estimation for Functions of Random Variables

Scibior, A., Simon-Gabriel, C., Tolstikhin, I., Schölkopf, B.

Advances in Neural Information Processing Systems 29, pages: 1732-1740, (Editors: D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett), Curran Associates, Inc., 30th Annual Conference on Neural Information Processing Systems (NIPS), 2016 (conference)

link (url) [BibTex]

link (url) [BibTex]


The population of long-period transiting exoplanets

Foreman-Mackey, D., Morton, T., Hogg, D., Agol, E., Schölkopf, B.

The Astrophysical Journal, 152(6):206, 2016 (article)

link (url) [BibTex]

link (url) [BibTex]


Multi-task logistic regression in brain-computer interfaces

Fiebig, K., Jayaram, V., Peters, J., Grosse-Wentrup, M.

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016), pages: 002307-002312, IEEE, 2016 (conference)

link (url) DOI [BibTex]

link (url) DOI [BibTex]