Suchergebnisse

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.

Berger, D.; Schulte-Pelkum, J.; Bülthoff, H.: Simulating believable forward accelerations on a Stewart motion platform (Technical Report of the Max Planck Institute for Biological Cybernetics, 159). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 19 S.

Breuer , P.; Kim, K.; Kienzle, W.; Blanz, V.; Schölkopf, B.: Automatic 3D Face Reconstruction from Single Images or Video (Technical Report of the Max Planck Institute for Biological Cybernetics, 160). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 12 S.

Sra, S.; Jain, P.; Dhillon, I.: Modeling data using directional distributions: Part II. University of Texas, Austin, TX, USA (2007), 15 S.

Kim, D.; Sra, S.; Dhillon, I.: A New Projected Quasi-Newton Approach for the Nonnegative Least Squares Problem. University of Texas, Austin, TX, USA (2006), 16 S.

Sinz, F.; Schölkopf, B.: Minimal Logical Constraint Covering Sets (Technical Report of the Max Planck Institute for Biological Cybernetics, 155). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2006), 12 S.

Toussaint, M.; Harmeling, S.; Storkey, A.: Probabilistic inference for solving (PO)MDPs. School of Informatics, Institute for Adaptive and Neural Computation, Edinburgh, UK (2006)

Biessmann, F.: New Methods for the P300 Visual Speller (Lab Report of the Max Planck Institute for Biological Cybernetics, 1). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2006), 21 S.