Suchergebnisse

Sra, S.: Block-Iterative Algorithms for Non-Negative Matrix Approximation (Technical Report of the Max Planck Institute for Biological Cybernetics, 176). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 16 S.

Sra, S.; Jegelka, S.; Banerjee, A.: Approximation Algorithms for Bregman Clustering Co-clustering and Tensor Clustering (Technical Report of the Max Planck Institute for Biological Cybernetics, 177). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 21 S.

Dhillon, P.; Nowozin, S.; Lampert, C.: Combining Appearance and Motion for Human Action Classification in Videos (Technical Report of the Max Planck Institute for Biological Cybernetics, 174). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 10 S.

Kim, K.; Kwon, Y.: Example-based Learning for Single-image Super-resolution and JPEG Artifact Removal (Technical Report of the Max Planck Institute for Biological Cybernetics, 173). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 28 S.

Chiappa, S.: Unsupervised Bayesian Time-series Segmentation based on Linear Gaussian State-space Models (Technical Report of the Max Planck Institute for Biological Cybernetics, 171). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008)

Kim, D.; Sra, S.; Dhillon, I.: A New Non-monotonic Gradient Projection Method for the Non-negative Least Squares Problem. University of Texas: Computer Sciences, Austin, TX, USA (2008)

Sra, S.; Kim, D.; Schölkopf, B.: Non-monotonic Poisson Likelihood Maximization (Technical Report of the Max Planck Institute for Biological Cybernetics, 170). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 18 S.

Gretton, A.; Borgwardt, K.; Rasch, M.; Schölkopf, B.; Smola, A.: A Kernel Method for the Two-sample Problem (Technical Report of the Max Planck Institute for Biological Cybernetics, 157). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 44 S.

Sinz, F.; Bethge, M.: How Much Can Orientation Selectivity and Contrast Gain Control Reduce the Redundancies in Natural Images (Technical Report of the Max Planck Institute for Biological Cybernetics, 169). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 28 S.

Hein, M.; Steinke, F.; Schölkopf, B.: Energy Functionals for Manifold-valued Mappings and Their Properties (Technical Report of the Max Planck Institute for Biological Cybernetics, 167). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 13 S.

Harmeling, S.; Touissant, M.: Bayesian Estimators for Robins-Ritov's Problem. School of Informatics, University of Edinburgh, Edinburgh, UK (2007), 12 S.

Kulis, B.; Sra, S.; Jegelka, S.; Dhillon, I.: Scalable Semidefinite Programming using Convex Perturbations. University of Texas, Austin, TX, USA (2007), 14 S.

Walder, C.; Chapelle, O.: Learning with Transformation Invariant Kernels (Technical Report of the Max Planck Institute for Biological Cybernetics, 165). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 12 S.

Blaschko, M.; Hofmann, T.; Lampert, C.: Efficient Subwindow Search for Object Localization (Technical Report of the Max Planck Institute for Biological Cybernetics, 164). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 14 S.

Walder, C.; Kim, K.; Schölkopf, B.: Sparse Multiscale Gaussian Process Regression (Technical Report of the Max Planck Institute for Biological Cybernetics, 162). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 14 S.

Kirschfeld, K.: Stellungnahme zur Broschüre "Affenversuche" des Deutschen Tierschutzbundes e.V. Landesbeirat für Tierschutz des Landes Baden-Württemberg, Stuttgart, Germany (2007), 7 S.

Maier, M.; Hein, M.; von Luxburg, U.: Cluster Identification in Nearest-Neighbor Graphs (Technical Report of the Max Planck Institute for Biological Cybernetics, 163). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 19 S.

Chiappa, S.; Barber, D.: Dirichlet Mixtures of Bayesian Linear Gaussian State-Space Models: a Variational Approach (Technical Report of the Max Planck Institute for Biological Cybernetics, 161). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 32 S.

Harmeling, S.: Exploring model selection techniques for nonlinear dimensionality reduction. School of Informatics, University of Edinburgh, Edinburgh, UK (2007), 20 S.

Meilinger, T.; Riecke, B.; Berger, D.; Bülthoff, H.: A novel immersive virtual environment setup for behavioural experiments in humans, tested on spatial memory for environmental spaces (Technical Report of the Max Planck Institute for Biological Cybernetics, 158). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 11 S.