65 results
(BibTeX)

**EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units**
*European Journal of Human Genetics*, 19(4):465-471, April 2011 (article)

**Multi-way set enumeration in weight tensors**
*Machine Learning*, 82(2):123-155, February 2011 (article)

**On Pairwise Kernels: An Efficient Alternative and Generalization Analysis**
In *Advances in Knowledge Discovery and Data Mining: 13th Pacific-Asia Conference*, pages: 1030-1037, (Editors: Theeramunkong, T. , B. Kijsirikul, N. Cercone, T. B. Ho), Springer, Berlin, Germany, PAKDD, April 2009 (inproceedings)

**Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction**
In *Proceedings of the 2009 SIAM International Conference on Data Mining*, pages: 1099-1110, (Editors: Park, H. , S. Parthasarathy, H. Liu), Philadelphia, PA, USA, Society for Industrial and Applied Mathematics, SDM, May 2009 (inproceedings)

**Data Mining for Biologists**
In *Biological Data Mining in Protein Interaction Networks*, pages: 14-27, (Editors: Li, X. and Ng, S.-K.), Medical Information Science Reference, Hershey, PA, USA, May 2009 (inbook)

**Protein Functional Class Prediction With a Combined Graph**
*Expert Systems with Applications*, 36(2):3284-3292, March 2009 (article)

**The DICS repository: module-assisted analysis of disease-related gene lists**
*Bioinformatics*, 25(6):830-831, January 2009 (article)

**A Bayesian Approach to Graph Regression with Relevant Subgraph Selection**
In *SIAM International Conference on Data Mining*, pages: 295-304, (Editors: Park, H. , S. Parthasarathy, H. Liu), Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, SDM, May 2009 (inproceedings)

**Enumeration of condition-dependent dense modules in protein interaction networks**
*Bioinformatics*, 25(7):933-940, February 2009 (article)

**Multi-way set enumeration in real-valued tensors**
In *Proceedings of the 2nd Workshop on Data Mining using Matrices and Tensors (DMMT 2009)*, pages: 32-41, (Editors: C Ding and T Li), ACM Press, New York, NY, USA, 2nd Workshop on Data Mining using Matrices and Tensors (DMMT/KDD), June 2009 (inproceedings)

**Partial Least Squares Regression for Graph Mining**
In *KDD2008*, pages: 578-586, (Editors: Li, Y. , B. Liu, S. Sarawagi), ACM Press, New York, NY, USA, 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2008 (inproceedings)

**Frequent Subgraph Retrieval in Geometric Graph Databases**
(180), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2008 (techreport)

**gBoost: A Mathematical Programming Approach to Graph Classification and Regression**
*Machine Learning*, 75(1):69-89, November 2008 (article)

**Frequent Subgraph Retrieval in Geometric Graph Databases**
In *ICDM 2008*, pages: 953-958, (Editors: Giannotti, F. , D. Gunopulos, F. Turini, C. Zaniolo, N. Ramakrishnan, X. Wu), IEEE Computer Society, Los Alamitos, CA, USA, 8th IEEE International Conference on Data Mining, December 2008 (inproceedings)

**Graph Mining with Variational Dirichlet Process Mixture Models**
In *SDM 2008*, pages: 432-442, (Editors: Zaki, M. J.), Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 8th SIAM International Conference on Data Mining, April 2008 (inproceedings)

**Logistic Regression for Graph Classification**
NIPS Workshop on "Structured Input - Structured Output" (NIPS SISO), December 2008 (talk)

**A Quantum-Statistical-Mechanical Extension of Gaussian Mixture Model**
*Journal of Physics: Conference Series*, 95(012023):1-9, January 2008 (article)

**Iterative Subgraph Mining for Principal Component Analysis**
In *ICDM 2008*, pages: 1007-1012, (Editors: Giannotti, F. , D. Gunopulos, F. Turini, C. Zaniolo, N. Ramakrishnan, X. Wu), IEEE Computer Society, Los Alamitos, CA, USA, IEEE International Conference on Data Mining, December 2008 (inproceedings)

**Change-Point Detection using Krylov Subspace Learning**
In *SDM 2007*, pages: 515-520, (Editors: Apte, C. ), Society for Industrial and Applied Mathematics, Pittsburgh, PA, USA, SIAM International Conference on Data Mining, April 2007 (inproceedings)

**Entire Regularization Paths for Graph Data**
In *ICML 2007*, pages: 919-926, (Editors: Ghahramani, Z. ), ACM Press, New York, NY, USA, 24th Annual International Conference on Machine Learning, June 2007 (inproceedings)

**Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism**
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)

**Mining complex genotypic features
for predicting HIV-1 drug resistance**
*Bioinformatics*, 23(18):2455-2462, September 2007 (article)

**Experimental design for efficient identification of gene regulatory networks using sparse Bayesian models**
*BMC Systems Biology*, 1(51):1-15, November 2007 (article)

**Discriminative Subsequence Mining for Action Classification**
In *ICCV 2007*, pages: 1919-1923, IEEE Computer Society, Los Alamitos, CA, USA, 11th IEEE International Conference on Computer Vision, October 2007 (inproceedings)

**Bayesian Inference and Optimal Design in the Sparse Linear Model**
In *JMLR Workshop and Conference Proceedings Volume 2: AISTATS 2007*, pages: 444-451, (Editors: Meila, M. , X. Shen), JMLR, Cambridge, MA, USA, 11th International Conference on Artificial Intelligence and Statistics, March 2007 (inproceedings)

**Weighted Substructure Mining for Image Analysis**
In *CVPR 2007*, pages: 1-8, IEEE Computer Society, Los Alamitos, CA, USA, 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 2007 (inproceedings)

**Mining expression-dependent modules in the human interaction network**
*BMC Bioinformatics*, 8(Suppl. 8):S4, November 2007 (poster)

**SCARNA: Fast and Accurate Structural Alignment of RNA Sequences by Matching Fixed-Length Stem Fragments**
*Bioinformatics*, 22(14):1723-1729, May 2006 (article)

**A Linear Programming Approach for Molecular QSAR analysis**
In *MLG 2006*, pages: 85-96, (Editors: Gärtner, T. , G. C. Garriga, T. Meinl), International Workshop on Mining and Learning with Graphs, September 2006, Best Paper Award (inproceedings)

**Prediction of Protein Function from Networks**
In *Semi-Supervised Learning*, pages: 361-376, Adaptive Computation and Machine Learning, (Editors: Chapelle, O. , B. Schölkopf, A. Zien), MIT Press, Cambridge, MA, USA, November 2006 (inbook)

**Network-based de-noising improves prediction from microarray data**
*BMC Bioinformatics*, 7(Suppl. 1):S4-S4, March 2006 (article)

**Graph boosting for molecular QSAR analysis**
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

**Clustering Graphs by Weighted Substructure Mining**
In *ICML 2006*, pages: 953-960, (Editors: Cohen, W. W., A. Moore), ACM Press, New York, NY, USA, 23rd International Conference on Machine Learning, June 2006 (inproceedings)

**Mining frequent stem patterns from unaligned RNA sequences**
*Bioinformatics*, 22(20):2480-2487, October 2006 (article)

**Image Reconstruction by Linear Programming**
*IEEE Transactions on Image Processing*, 14(6):737-744, June 2005 (article)

**Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection**
*Journal of Machine Learning Research*, 6, pages: 995-1018, June 2005 (article)

**Propagating Distributions on a Hypergraph by Dual Information Regularization**
In *Proceedings of the 22nd International Conference on Machine Learning*, pages: 921 , (Editors: De Raedt, L. , S. Wrobel), ICML Bonn, 2005 (inproceedings)

**Selective integration of multiple biological data for supervised
network inference**
*Bioinformatics*, 21(10):2488 , October 2005 (article)

**Fast Protein Classification with Multiple Networks**
*Bioinformatics*, 21(Suppl. 2):59-65, September 2005 (article)

**Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection **
In *Advances in Neural Information Processing Systems 17*, pages: 1425-1432, (Editors: Saul, L.K. , Y. Weiss, L. Bottou), MIT Press, Cambridge, MA, USA, Eighteenth Annual Conference on Neural Information Processing Systems (NIPS), July 2005 (inproceedings)

**Kernel Methods in Computational Biology**
pages: 410, Computational Molecular Biology, MIT Press, Cambridge, MA, USA, August 2004 (book)

**Asymptotic Properties of the Fisher Kernel**
*Neural Computation*, 16(1):115-137, 2004 (article)

**Learning kernels from biological networks by maximizing entropy**
*Bioinformatics*, 20(Suppl. 1):i326-i333, August 2004 (article)

**Protein Functional Class Prediction with a Combined Graph**
In *Proceedings of the Korean Data Mining Conference*, pages: 200-219, Proceedings of the Korean Data Mining Conference, 2004 (inproceedings)

**Minimizing the Cross Validation Error to Mix Kernel Matrices of Heterogeneous Biological Data**
*Neural Processing Letters*, 19, pages: 63-72, 2004 (article)

**A New Variational Framework for Rigid-Body Alignment**
In *Joint IAPR International Workshops on Syntactical and Structural Pattern Recognition (SSPR 2004) and Statistical Pattern Recognition (SPR 2004)*, pages: 171-179, (Editors: Fred, A.,T. Caelli, R.P.W. Duin, A. Campilho and D. de Ridder), Joint IAPR International Workshops on Syntactical and Structural Pattern Recognition (SSPR) and Statistical Pattern Recognition (SPR), 2004 (inproceedings)

**Protein Classification via Kernel Matrix Completion**
In pages: 261-274, (Editors: Schoelkopf, B., K. Tsuda and J.P. Vert), MIT Press, Cambridge, MA; USA, 2004 (inbook)

**Learning to Find Graph Pre-Images**
In *Pattern Recognition*, pages: 253-261, (Editors: Rasmussen, C. E., H. H. Bülthoff, B. Schölkopf, M. A. Giese), Springer, Berlin, Germany, 26th DAGM Symposium, August 2004 (inproceedings)

**A Primer on Kernel Methods**
In *Kernel Methods in Computational Biology*, pages: 35-70, (Editors: B Schölkopf and K Tsuda and JP Vert), MIT Press, Cambridge, MA, USA, 2004 (inbook)

**Image Construction by Linear Programming**
In *Advances in Neural Information Processing Systems 16*, pages: 57-64, (Editors: Thrun, S., L.K. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)