COLT 2003 ScheduleSunday, 24.08.200319:00 - 22:00 Reception (Powerscourt) Monday, 25.08.2003TARGET AREA: COMPUTATIONAL GAME THEORY (Ballroom)(Session chair: Michael Kearns)
KERNEL MACHINES I (Ballroom)(Session chair: Kristin Bennett)
KERNEL MACHINES II (Ballroom)(Session chair: Corinna Cortes)
20:00 POSTER SESSION I (Powerscourt)Poster session for all of Monday's talks- plus posters of the open problems - plus all Kernel impromptu posters: SVM Learning in Distributed Environments Tsuyoshi Okita, Bernard Manderick, Vrije Universiteit Brussel - plus the following additional posters: Comparing clusterings by the Variation of Information Marina Meila, University of Washington Multiplicative Updates for Large Margin Classifiers Fei Sha, Lawrence Saul, Daniel Lee, University of Pennsylvania Simplified PAC-Bayesian Margin Bounds David McAllester, Toyota Technological Institute at Chicago Sparse Kernel Partial Least Squares Regression Michinari Momma, Kristin Bennett, Rensselaer Polytechnic Institute Sparse Probabilistic Regression by Label Partitioning Shantanu Chakrabartty, Gert Cauwenberghs, The Johns Hopkins University, Prof Jayadeva, Indian Institute of Technology Learning with Rigorous Support Vector Machines Jinbo Bi, Rensselaer Polytechnic Insitute, Vladimir Vapnik, NEC Laboratories America Robust Regression by Boosting the Median Balazs Kegl, University of Montreal Boosting with Diverse Base Classifiers Sanjoy Dasgupta, University of California at San Diego, Philip Long, Genome Institute of Singapore Reducing Kernel Matrix Diagonal Dominance using Semi-Definite Programming Jaz Kandola, Royal Holloway, University of London, Thore Graepel, Microsoft Research, John Shawe-Taylor, Royal Holloway, University of London Tuesday, 26.08.2003STATISTICAL LEARNING THEORY (Ballroom)(Session chair: Gabor Lugosi)
ONLINE LEARNING (Ballroom)(Session chair: Ron Meir)
OTHER APPROACHES (Ballroom)(Session chair: Alex Smola)
19:30 IMPROMPTU TALKS (Ballroom)(Session chair: Yoav Freund)20:00 POSTER SESSION II (Powerscourt)Poster session for all Tuesday's and Wednesday's talks- plus the following additional posters: Using A Linear Fit To Determine Monotonicity Directions Malik Magdon-Ismail, RPI, Joseph Sill, Plumtree Software Generalization bounds for voting classifiers based on sparsity and clustering Vladimir Koltchinskii, The University of New Mexico, Dmitry Panchenko, Massachusetts Institute of Technology, Savina Andonova, Boston University Sequence Prediction based on Monotone Complexity Marcus Hutter, IDSIA How Many Strings Are Easy to Predict? Yuri Kalnishkan, Volodya Vovk, Michael V. Vyugin, Royal Holloway University of London Polynomial Certificates for Propositional Classes Marta Arias, Roni Khardon, Tufts University, Rocco A. Servedio, Columbia University On-line Learning with Imperfect Monitoring Shie Mannor, Massachusetts Institute of Technology, Nahum Shimkin, Technion Exploiting Task Relatedness for Multiple Task Learning Shai Ben-David, Cornell University and Technion, Reba Schuller, Cornell University Approximate Equivalence of Markov Decision Processes Eyal Even-Dar, Yishay Mansour, Tel Aviv University An Information Theoretic Tradeoff between Complexity and Accuracy Ran Gilad-Bachrach, Amir Navot, Naftali Tishby, The Hebrew University of Jerusalem Learning Random log-depth Decision Trees under the Uniform Distribution Jeffrey Jackson, Duquesne University, Rocco Servedio, Columbia University Projective DNF Formulae and Their Revision Robert Sloan, University of Illinois at Chicago, Balazs Szorenyi, University of Szeged, Gyorgy Turan, University of Illinois at Chicago Learning with Equivalence Constraints, and the Relation to Multiclass Learning Aharon Bar Hillel, Daphna Weinshall, The Hebrew University of Jerusalem Wednesday, 27.08.2003TARGET AREA: NATURAL LANGUAGE PROCESSING (Ballroom)(Session chair: Rob Schapire)
INDUCTIVE INFERENCE LEARNING (Ballroom)(Session chair: Nicolò Cesa-Bianchi)
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