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Matthew Blaschko
Position: PhD Student
Phone: +49-7071-601 543
Fax: +49-7071-601 552

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2011
Articles
2010
Posters
  • JA. Shelton, MB. Blaschko, A. Bartels (2010). Augmentation of fMRI Data Analysis using Resting State Activity and Semi-supervised Canonical Correlation Analysis NIPS 2010 Women in Machine Learning Workshop (WiML 2010)
Articles
2009
Articles
  • CH. Lampert, MB. Blaschko, T. Hofmann (2009). Efficient Subwindow Search: A Branch and Bound Framework for Object Localization IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, (12), 2129-2142
Conference Papers
  • MB. Blaschko, A. Gretton (2009). Learning Taxonomies by Dependence Maximization In: Advances in neural information processing systems 21, (Ed) Koller, D. , D. Schuurmans, Y. Bengio, L. Bottou, Advances in neural information processing systems 21 : 22nd Annual Conference on Neural Information Processing Systems 2008, Curran, Red Hook, NY, USA, 153-160, ISBN: 978-1-605-60949-2, Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008)
  • M. Blaschko, CH. Lampert (2009). Object Localization with Global and Local Context Kernels In: BMVC 2009, Proceedings of the British Machine Vision Conference 2009 (BMVC 2009), 1-11, British Machine Vision Conference 2009
  • M. Blaschko, J. Shelton, A. Bartels (2009). Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity In: Advances in Neural Information Processing Systems 22, (Ed) Bengio, Y. , D. Schuurmans, J. Lafferty, C. Williams, A. Culotta, Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009, Curran, Red Hook, NY, USA, 126-134, ISBN: 978-1-615-67911-9, 23rd Annual Conference on Neural Information Processing Systems (NIPS 2009)
Theses
  • MB. Blaschko (2009). Kernel Methods in Computer Vision: Object Localization, Clustering, and Taxonomy Discovery Technische Universität Berlin, Berlin, Germany, (Ph.D Thesis)
Posters
Technical Reports
  • J. Shelton, M. Blaschko, A. Bartels (2009). Semi-supervised subspace analysis of human functional magnetic resonance imaging data Max Planck Institute for Biological Cybernetics, Tübingen, Germany
2008
Conference Papers
  • MB. Blaschko, CH. Lampert (2008). Learning to Localize Objects with Structured Output Regression In: ECCV 2008, (Ed) Forsyth, D. A., P. H.S. Torr, A. Zisserman, Computer Vision: ECCV 2008, Springer, Berlin, Germany, 2-15, 10th European Conference on Computer Vision
  • MB. Blaschko, CH. Lampert, A. Gretton (2008). Semi-Supervised Laplacian Regularization of Kernel Canonical Correlation Analysis In: ECML PKDD 2008, (Ed) Daelemans, W. , B. Goethals, K. Morik, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2008, Springer, Berlin, Germany, 133-145, 19th European Conference on Machine Learning
  • CH. Lampert, M. Blaschko (2008). Joint Kernel Support Estimation for Structured Prediction Proceedings of the NIPS 2008 Workshop on "Structured Input - Structured Output" (NIPS SISO 2008), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, 1-4, NIPS 2008 Workshop on "Structured Input - Structured Output" (NIPS SISO 2008)
  • C. Lampert, MB. Blaschko (2008). A Multiple Kernel Learning Approach to Joint Multi-Class Object Detection In: DAGM 2008, (Ed) Rigoll, G. , Pattern Recognition: Proceedings of the 30th DAGM Symposium, Springer, German Association for Pattern Recognition, Berlin, Germany, 31-40, 30th Annual Symposium of the German Association for Pattern Recognition
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  • MB. Blaschko, A. Gretton (2008). A Hilbert-Schmidt Dependence Maximization Approach to Unsupervised Structure Discovery In: MLG 2008, Proceedings of the 6th International Workshop on Mining and Learning with Graphs (MLG 2008), 1-3, 6th International Workshop on Mining and Learning with Graphs
  • MB. Blaschko, CH. Lampert (2008). Correlational Spectral Clustering In: CVPR 2008, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), IEEE Computer Society, Los Alamitos, CA, USA, 1-8, IEEE Computer Society Conference on Computer Vision and Pattern Recognition
  • CH. Lampert, MB. Blaschko, T. Hofmann (2008). Beyond Sliding Windows: Object Localization by Efficient Subwindow Search In: CVPR 2008, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), IEEE Computer Society, Los Alamitos, CA, USA, 1-8, IEEE Computer Society Conference on Computer Vision and Pattern Recognition
    [DOI] [PDF] [PDF] [Web] [BibTex] [Share]
Technical Reports
2007
Technical Reports
2006
Conference Papers
  • MB. Blaschko, T. Hofmann (2006). Conformal Multi-Instance Kernels NIPS 2006 Workshop on Learning to Compare Examples, 1-6, NIPS 2006 Workshop on Learning to Compare Examples
2005
Conference Papers
  • DA. Lisin, MA. Mattar, MB. Blaschko, MC. Benfield, EG. Learned-Miller (2005). Combining Local and Global Image Features for Object Class Recognition In: CVPR, Proceedings of IEEE Workshop on Learning in Computer Vision and Pattern Recognition (in conjunction with CVPR), 47-47, CVPR
  • MB. Blaschko, G. Holness, MA. Mattar, D. Lisin, PE. Utgoff, AR. Hanson, H. Schultz, EM. Riseman, ME. Sieracki, WM. Balch, B. Tupper (2005). Automatic In Situ Identification of Plankton In: WACV, Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION‘05), 79 , WACV
Theses
  • MB. Blaschko (2005). Support Vector Classification of Images with Local Features University of Massachusetts, Amherst, (Diplom Thesis)
Posters
  • M. Sieracki, E. Riseman, W. Balch, M. Benfield, A. Hanson, C. Pilskaln, H. Schultz, C. Sieracki, P. Utgoff, M. Blaschko, G. Holness, M. Mattar, D. Lisin, B. Tupper (2005). Automatic Classification of Plankton from Digital Images ASLO Aquatic Sciences Meeting, 1, 1
2004
Conference Papers
  • MD. Shapiro, MB. Blaschko (2004). Stability of Hausdorff-based Distance Measures In: VIIP, Visualization, Imaging, and Image Processing, 1-6, VIIP
Technical Reports
  • MD. Shapiro, MB. Blaschko (2004). On Hausdorff Distance Measures Department of Computer Science, University of Massachusetts Amherst