Department of Electrical and Computer Engineering
University of California, San Diego
5604 EBU1
Mailcode 0407
La Jolla, CA 92093-0407
USA
Fax: + 1 858 534-6976
Phone: + 1 858 539-6003
Sriperumbudur Vangeepuram, B., Lanckriet, G.R.G. (2009) On the Convergence of the Concave-Convex Procedure. Advances in Neural Information Processing Systems 22, Cambridge, MA: MIT Press.
Sriperumbudur Vangeepuram, B., Gretton, A., Fukumizu, K., Lanckriet, G.R.G., Schölkopf, B. (2009) Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions. Advances in Neural Information Processing Systems 22, Cambridge, MA: MIT Press.
McFee, B., Lanckriet, G.R.G. (2009) Heterogeneous Embedding for Subjective Artist Similarity. Proceedings of the 10th International Conference on Music Information Retrieval, Kobe, Japan.
Barrington, L., Oda, R., Lanckriet, G.R.G. (2009) Smarter Than Genius? Human Evaluation of Music Recommender Systems. Proceedings of the 10th International Conference on Music Information Retrieval, Kobe, Japan.
Barrington, L., Turnbull, D., Yazdani, M., Lanckriet, G.R.G. (2009) Combining Audio Content and Social Context for Semantic Music Discovery. Proceedings of the 32nd Annual International ACM SIGIR Conference on Research & Development on Information Retrieval, Boston, MA.
McFee, B., Lanckriet, G.R.G. (2009) Partial Order Embedding with Multiple Kernels. Proceedings of the 26th International Conference on Machine Learning, Montreal, Canada.
Barrington, L., Chan, A. B., Lanckriet, G.R.G. (2009) Dynamic Texture Models of Music. Proceedings of the 34th International Conference on Acoustics, Speech, and Signal Processing, Taipei, Taiwan.
Sriperumbudur Vangeepuram, B., Torres, D., Lanckriet, G.R.G. (2009) The sparse eigenvalue problem. Technical Report (Arxiv).
Barrington, L., Yazdani, M., Turnbull, D., Lanckriet, G.R.G. (2008) Combining Feature Kernels for Semantic Music Retrieval. Proceedings of the 9th International Conference on Music Information Retrieval, Philadelphia, PA.
Turnbull, D., Barrington, L., Lanckriet, G.R.G. (2008) Five Approaches to Collecting Tags for Music. Proceedings of the 9th International Conference on Music Information Retrieval, Philadelphia, PA.
Sriperumbudur Vangeepuram, B., Gretton, A., Fukumizu, K., Lanckriet, G.R.G., Scholkopf, B. (2008). Injective Hilbert Space Embeddings of Probability Measures. Proceedings of the 21st Annual Conference on Learning Theory, Helsinki, Finland.
Sriperumbudur Vangeepuram, B., Lang, O., Lanckriet, G.R.G. (2008). Metric Embedding for Kernel Classification Rules. Proceedings of the 25th International Conference on Machine Learning, Helsinki, Finland.
Obozinski, G., Lanckriet, G.R.G., Grant, C.E., Jordan, M.I., Noble, W.S. (2008). Consistent Probabilistic Outputs for Protein Function Prediction. Genome Biology, Vol. 9(Suppl.1):S6. (Supplement on Methods, Supplementary Figures, Supplementary Data)
Pena-Castillo, L., et al. (2008). A Critical Assessment of M. Musculus Gene Function Prediction using Integrated Genomic Evidence. Genome Biology, Vol. 9(Suppl.1):S2.
Turnbull, D., Barrington, L., Torres, D., Lanckriet, G.R.G. (2008). Semantic Annotation and Retrieval of Music and Sound Effects. IEEE Transactions on Audio, Speech and Language Processing, Vol. 16, pp. 467-476.
Torres, D., Turnbull, D., Barrington, L., Lanckriet, G.R.G. (2007). Identifying Words that are Musically Meaningful. Proceedings of the 8th International Conference on Music Information Retrieval, Vienna, Austria.
Turnbull, D., Liu, R., Barrington, L., Lanckriet, G.R.G. (2007). A Game-Based Approach for Collecting Semantic Annotations of Music. Proceedings of the 8th International Conference on Music Information Retrieval, Vienna, Austria.
Turnbull, D., Lanckriet, G.R.G., Pampalk, E., Goto, M. (2007). A Supervised Approach for Detecting Boundaries in Music using Difference Features and Boosting. Proceedings of the 8th International Conference on Music Information Retrieval, Vienna, Austria.
Sriperumbudur Vangeepuram, B., Torres, D., Lanckriet, G.R.G. (2007). Sparse Eigenmethods by D.C. Programming. Proceedings of the 24th International Conference on Machine Learning, Corvallis, OR.
Chan, A., Vasconcelos, N., Lanckriet, G.R.G. (2007). Direct Convex Relaxations of Sparse SVM. Proceedings of the 24th International Conference on Machine Learning, Corvallis, OR.
Turnbull, D., Barrington, L., Torres, D., Lanckriet, G.R.G. (2007). Towards Musical Query-by-Semantic-Description using the CAL500 Data Set. Proceedings of the 30th Annual International ACM SIGIR Conference on Research & Development on Information Retrieval, Amsterdam, The Netherlands.
d'Aspremont, A., El Ghaoui, L., Jordan, M.I., Lanckriet, G.R.G. (2007). A Direct Formulation for Sparse PCA using Semidefinite Programming. SIAM Review, vol. 49, pp. 434-448.
Barrington, L., Chan, A., Turnbull, D., Lanckriet, G.R.G. (2007). Audio Information Retrieval Using Semantic Similarity. Proceedings of the 32nd International Conference on Acoustics, Speech, and Signal Processing, Honolulu, Hawaii.
Agarwal, S., Wills, J., Cayton, L., Lanckriet, G.R.G., Kriegman, D., Belongie, S. (2007). Generalized Non-metric Multidimensional Scaling. Proceedings of the 11th International Conference on Artificial Intelligence and Statistics, San Juan, Puerto Rico.
Turnbull, D., Barrington, L., Lanckriet, G.R.G. (2006). Modeling Music and Words. Proceedings of the 7th International Conference on Music Information Retrieval, Victoria, Canada.
Dal Moro, F., Abate, A., Lanckriet, G.R.G., Arandjelovic, G., Gasparella, P., Bassi, P., Mancini, M., Pagano, F. (2006). A novel approach for accurate prediction of spontaneous passage of ureteral stones: Support vector machines. Kidney International, vol. 69, pp. 157-160.
Natsoulis, G., El Ghaoui, L., Lanckriet, G.R.G., Tolley, A.M., Leroy, F., Dunlea, S., Eynon, B.P., Pearson, C.I., Tugendreich, S., Jarnagin, K. (2005). Classification of a large micro-array dataset. Algorithm comparison and analysis of drug signatures. Genome Research, vol. 15, pp. 724-736.
d'Aspremont, A., El Ghaoui, L., Jordan, M.I., Lanckriet, G.R.G. (2004). A Direct Formulation for Sparse PCA using Semidefinite Programming . Advances in Neural Information Processing Systems 17, Cambridge, MA: MIT Press. [ DSPCA code ]
Lanckriet, G.R.G., De Bie, T., Cristianini, N. , Jordan, M.I., Noble, W.S. (2004). A statistical framework for genomic data fusion . Bioinformatics, 20, 2626-2635, 2004. [ supplementary information ]
Gwiggner, C., Lanckriet, G.R.G. (2004). Characteristics in flight data - Estimation with Logistic Regression and Support Vector Machines . Proceedings of the 1st International Conference on Research in Air Transportation (ICRAT), Zilina, Slovakia: Zilina University Press.
d'Aspremont, A., El Ghaoui, L., Jordan, M.I., Lanckriet, G.R.G. (2004). A Direct Formulation for Sparse PCA using Semidefinite Programming . Technical Report CSD-04-1330, Division of Computer Science, University of California, Berkeley.
Bach, F.R. & Lanckriet, G.R.G., Jordan, M.I. (2004). Multiple Kernel Learning, Conic Duality, and the SMO Algorithm. In Proceedings of the 21st International Conference on Machine Learning, Banff, Canada: Omnipress. [code can be found on Guillaume Obozinski's website (scroll to the bottom) ]
Bach, F.R. & Lanckriet, G.R.G., Jordan, M.I. (2004). Fast Kernel Learning using Sequential Minimal Optimization. Technical Report CSD-04-1307, Division of Computer Science, University of California, Berkeley.
Lanckriet, G.R.G., Cristianini, N., Bartlett, P., El Ghaoui, L., Jordan, M.I. (2004). Learning the Kernel Matrix with Semidefinite Programming . Journal of Machine Learning Research, 5, 27-72, 2004.
De Bie, T., Lanckriet, G.R.G., Cristianini, N. (2003). Convex Tuning of the Soft Margin Parameter . Technical Report CSD-03-1289, Division of Computer Science, University of California, Berkeley.
Lanckriet, G.R.G., Deng, M., Cristianini, N. , Jordan, M.I., Noble, W.S. (2004). Kernel-based Data Fusion and its Application to Protein Function Prediction in Yeast . In press: Proceedings of the Pacific Symposium on Biocomputing (PSB). [ supplementary information ]
El Ghaoui, L., Lanckriet, G.R.G., Natsoulis, G. (2003). Robust Classification with Interval Data . Technical Report CSD-03-1279, Division of Computer Science, University of California, Berkeley.
Lanckriet, G.R.G., Cristianini, N., Jordan, M.I., Noble, W.S. (2004). Kernel-based Integration of Genomic Data using Semidefinite Programming . In B. Schoelkopf, K. Tsuda and J.-P. Vert (Eds.), Kernel Methods in Computational Biology: MIT Press.
Lanckriet, G.R.G., De Bie, T., Cristianini, N., Jordan, M.I., Noble, W.S. (2003). A Framework for Genomic Data Fusion and its Application to Membrane Protein Prediction . Technical Report CSD-03-1273, Division of Computer Science, University of California, Berkeley.
Lanckriet, G.R.G., El Ghaoui, L., Bhattacharyya, C., Jordan, M.I. (2002). A Robust Minimax Approach to Classification . Journal of Machine Learning Research, 3, 555-582, 2002. [ matlab code, version 1.0 ]
Lanckriet, G.R.G., El Ghaoui, L., Bhattacharyya, C., Jordan, M.I. (2002). A Robust Minimax Approach to Classification . Technical Report CSD-02-1218, Division of Computer Science, University of California, Berkeley.
Lanckriet, G.R.G., Cristianini, N., Bartlett, P., El Ghaoui, L., Jordan, M.I. (2002). Learning the Kernel Matrix with Semi-Definite Programming . Technical Report CSD-02-1206, Division of Computer Science, University of California, Berkeley.
Lanckriet, G.R.G., El Ghaoui, L., Jordan, M.I. (2002). Robust Novelty Detection with Single-Class MPM . Advances in Neural Information Processing Systems 15, Cambridge, MA: MIT Press.
Lanckriet, G.R.G., Cristianini, N., Bartlett, P., El Ghaoui, L., Jordan, M.I. (2002). Learning the Kernel Matrix with Semidefinite Programming . In C. Sammut and A. Hoffmann (Eds.), Proceedings of the 19th International Conference on Machine Learning, Sydney, Australia: Morgan Kaufmann.
Lanckriet, G.R.G., El Ghaoui, L., Bhattacharyya, C., Jordan, M.I. (2002). Minimax Probability Machine . In T. Dietterich, S. Becker and Z. Ghahramani (Eds.), Advances in Neural Information Processing Systems 14, Cambridge, MA: MIT Press. [ matlab code, version 1.0 ]
Van Gestel, T., Suykens, J.A.K., Lanckriet, G.R.G. , Lambrechts, A., De Moor, B., Vandewalle, J. (2002). A Bayesian Framework for Least Squares Support Vector Machine Classifiers , Neural Computation, vol. 15(4), pp. 1115-1147.
Van Gestel, T., Suykens, J.A.K., Lanckriet, G.R.G., Lambrechts, A., De Moor, B., Vandewalle, J. (2002). Multiclass LS-SVMs: Moderated Outputs and Coding-Decoding Schemes , Neural Processing Letters , vol. 15, pp. 45-58.
Van Gestel, T., Suykens, J.A.K., Lanckriet, G.R.G. , Lambrechts, A., Baestaens, D., De Moor, B., Vandewalle, J. (2001). Bayesian Interpretation of Least Squares Support Vector Machines for Financial Time Series Prediction . Proceedings of the 5th World Multi-Conference on Systemics, Cybernetics and Informatics , Vol. III, pp. 254-259, Orlando, Florida. Outstanding paper award.
Van Gestel, T., Suykens, J.A.K., Baestaens, D.-E., Lambrechts, A., Lanckriet, G.R.G., Vandaele, B., De Moor, B., Vandewalle J. (2001). Financial Time Series Prediction using Least Squares Support Vector Machines within the Evidence Framework , IEEE Transactions on Neural Networks ( Special Issue on Financial Engineering) , vol. 12(4), pp. 809-821.