From sarahd at dimacs.rutgers.edu Fri May 2 15:21:08 2003 From: sarahd at dimacs.rutgers.edu (Sarah Donnelly) Date: Fri, 2 May 2003 15:21:08 -0400 (EDT) Subject: [Sy-cg-global] PROGRAM: DIMACS Workshop on Geometric Optimization Message-ID: <200305021921.PAA02536@dimacs.rutgers.edu> DIMACS Workshop on Geometric Optimization May 19 - 21, 2003 DIMACS Center, CoRE Building, Rutgers University Organizers: Joe Mitchell, SUNY Stony Brook, jsbm at ams.sunysb.edu Pankaj Agarwal, Duke University, pankaj at cs.duke.edu Presented under the auspices of the Special Focus on Computational Geometry and Applications. **************************************************************** Combinatorial optimization typically deals with problems of maximizing or minimizing a function of one or more variables subject to a large number of constraints. In many applications, the underlying optimization problem involves a constant number of variables and a large number of constraints that are induced by a given collection of geometric objects; these problems are referred to as geometric-optimization problems. Typical examples include facility location, low-dimensional clustering, network-design, optimal path-planning, shape-matching, proximity, and statistical-measure problems. In such cases one expects that faster and simpler algorithms can be developed by exploiting the geometric nature of the problem. Much work has been done on geometric-optimization problems during the last twenty-five years. Many elegant and sophisticated techniques have been proposed and successfully applied to a wide range of geometric-optimization problems. Several randomization and approximation techniques have been proposed. In parallel with the effort in the geometric algorithms community, the mathematical programming and combinatorial optimization communities have made numerous fundamental advances in optimization, both in computation and in theory, during the last quarter century. Interior-point methods, polyhedral combinatorics, and semidefinite programming have been developed as powerful mathematical and computational tools for optimization, and some of them have been used for geometric problems. Scope and Format: This workshop aims to bring together people from different research communities interested in geometric-optimization problems. The goal is to discuss various techniques developed for geometric optimization and their applications, to identify key research issues that need to be addressed, and to help establish relationships which can be used to strengthen and foster collaboration across the different areas. **************************************************************** Registration Fees: (Pre-registration deadline: May 12, 2003) Regular rate Preregister before deadline $120/day After preregistration deadline $140/day Reduced Rate* Preregister before deadline $60/day After preregistration deadline $70/day Postdocs Preregister before deadline $10/day After preregistration deadline $15/day DIMACS Postdocs $0 Non-Local Graduate & Undergraduate students Preregister before deadline $5/day After preregistration deadline $10/day Local Graduate & Undergraduate students $0 (Rutgers & Princeton) DIMACS partner institution employees** $0 DIMACS long-term visitors*** $0 Registration fee to be collected on site, cash, check, VISA/Mastercard accepted. Our funding agencies require that we charge a registration fee for the workshop. Registration fees cover participation in the workshop, all workshop materials, breakfast, lunch, breaks, and any scheduled social events (if applicable). * College/University faculty and employees of non-profit organizations will automatically receive the reduced rate. Other participants may apply for a reduction of fees. They should email their request for the reduced fee to the Workshop Coordinator at workshop at dimacs.rutgers.edu. Include your name, the Institution you work for, your job title and a brief explanation of your situation. All requests for reduced rates must be received before the preregistration deadline. You will promptly be notified as to the decision about it. ** Fees for employees of DIMACS partner institutions are waived. DIMACS partner institutions are: Rutgers University, Princeton University, AT&T Labs - Research, Bell Labs, NEC Laboratories America and Telcordia Technologies. Fees for employees of DIMACS affiliate members Avaya Labs, IBM Research and Microsoft Research are also waived. ***DIMACS long-term visitors who are in residence at DIMACS for two or more weeks inclusive of dates of workshop. ********************************************************* PROGRAM Monday, May 19, 2003 8:15-8:55 Breakfast and Registration 8:55-9:00 Opening remarks: Fred S. Roberts, Director of DIMACS 9:00-10:00 Unique Sink Orientations of Cubes and its Relations to Optimization Emo Welzl, ETH Zurich 10:00-10:30 Smoothed Analysis of Algorithms: Simplex Algorithm and Numerical Analysis Shanghua Teng, Boston University 10:30-11:00 Break 11:00-11:30 The Protein Side-Chain Positioning Proble Carl Kingsford, Princeton University 11:30-12:00 Approximate Protein Structural Alignment in Polynomial Time Rachel Kolodny, Stanford University 12:00-12:30 Hausdorff Distance under Translation for Points and Balls Yusu Wang, Duke University 12:30-02:00 Lunch 02:00-03:00 Emerging Trends in Optimization Dan Bienstock, Columbia University 03:00-03:30 Exact Parallel Algorithm for Computing Maximum Feasible Subsystems of Linear Relations Vera Rosta, McGill University 03:30-04:00 Improved Embeddings of Metrics into Trees Satish Rao, UC Berkeley 04:00-04:30 Break 04:30-05:00 Online Searching with Turn Cost Erik Demaine, MIT 05:00-05:30 Leave no Stones Unturned: Improved Approximation Algorithms for Degree-Bounded Minimum Spanning Trees Raja Jothi, UT Dallas 05:30-06:00 Constructing Spanners of Different Flavors Joachim Gudmundsson Tuesday, May 20, 2003 08:15-09:00 Breakfast and registration 09:00-10:00 Random Walks and Geometric Algorithms Santosh Vempala, MIT 10:00-10:30 Approximation Algorithms for k-Center Clustering Piyush Kumar, SUNY Sony Brook 10:30-11:00 Break 11:00-11:30 Computing Projective Clusters via Certificates Cecilia M. Procopiuc, AT&T Labs 11:30-12:00 Shape Fitting with Outliers Sariel Har-Peled, UIUC 12:00-12:30 Approximate Minimum Volume Enclosing Ellipsoids Using Core Sets Alper Yildirim, SUNY Sony Brook 12:30-02:00 Lunch 02:00-03:00 Geometric Optimization and Arrangements Micha Sharir, Tel Aviv University 03:00-03:30 Approximating the k-Radius of High-Dimensional Point Sets Kasturi Varadarajan, University of Iowa 03:30-04:00 Break 04:00-05:00 Approximation Schemes for Geometric NP-Hard Problems: A Survey Sanjeev Arora, Princeton University 05:00-05:30 TSP with Neighborhoods of Varying Size Matya Katz, Ben Gurion University 05:30-06:00 Touring a Sequence of Polygons Alon Efrat, University of Arizona Wednesday, May 21, 2003 09:00-10:00 Quasiconvex Programming David Eppstein, UC Irvine 10:00-10:30 Engineering Geometric Optimization Algorithms: Some Experiments Herve Bronnimann, Polytechnic University 10:30-11:00 Subtraction in Geometric Searching Bernard Chazelle 11:00-11:30 Minimum Separation in Weighted Subdivisions Ovidiu Daescu and James Palmer 11:30-12:30 Lunch 12:30-01:00 Some Data Streaming Problems in Computational Geometry S. Muthukrishnan, Rutgers University 01:00-01:30 Streaming Geometric Optimization Using Graphics Hardware Suresh Venkatasubramanian, AT&T Labs 01:30-02:00 Efficient Algorithms for Shared Camera Control Vladlen Koltun, UC Berkeley ********************************************************* Information on participation, registration, accommodations, and travel can be found at: http://dimacs.rutgers.edu/Workshops/GeomOpt/ **PLEASE BE SURE TO PRE-REGISTER EARLY** ********************************************************* From lindac at dimacs.rutgers.edu Wed May 7 14:18:07 2003 From: lindac at dimacs.rutgers.edu (Linda Casals) Date: Wed, 7 May 2003 14:18:07 -0400 (EDT) Subject: [Sy-cg-global] [Publicity-list] DIMACS Workshop on Data Depth: Robust Multivariate Analysis, Computational Geometry and Applications Message-ID: <200305071818.OAA29821@dimacs.rutgers.edu> ************************************************************* DIMACS Workshop on Data Depth: Robust Multivariate Analysis, Computational Geometry and Applications May 14 - 16, 2003 DIMACS Center, Rutgers University, Piscataway, NJ Organizers: Regina Liu Rutgers University, rliu at stat.rutgers.edu Robert Serfling University of Texas at Dallas serfling at utdallas.edu Diane Souvaine Tufts University dls at eecs.tufts.edu Yehuda Vardi Rutgers University vardi at stat.rutgers.edu Presented under the auspices of the DIMACS Special Focus on Data Analysis and Mining and the DIMACS Special Focus on Computational Geometry and Applications. ****************************************************** Multivariate statistical methodology plays a role of ever increasing importance in real life applications, which typically entail a host of interrelated variables. Simple extensions of univariate statistics to the multivariate setting do not properly capture the higher-dimensional features of multivariate data, nor do they yield geometric solutions because of the absence of a natural order for multidimensional Euclidean space. A more promising approach is the one based on "data depth", which can provide a center-outward ordering of points in Euclidean space of any dimension. Extensive developments in recent years have generated many attractive depth-based tools for multivariate data analysis, with a wide range of applications. The diversity in approaches, emphases, and concepts, however, makes it necessary to seek unified views and perspectives that would guide the further development of the depth-based approach. The concept of data depth provides new perspectives to probabilistic as well as computational geometries. In particular, the development of implementable computing algorithms for depth-based statistics has brought about many new challenges in computational geometry. This workshop would create a unique environment for multidisciplinary collaboration among computer scientists, theoretical and applied statisticians, and data analysts. It would bring together active researchers in these fields to discuss significant open issues, establish perspective on applications, and set directions for further research. ****************************************************** STUDENT SCHOLARSHIPS: The workshop offers some student scholarships to reimburse expenses for travel, registration, and lodging at the workshop, up to $400. Applicants for student scholarships should contact Regina Liu (rliu at stat.rutgers.edu). ****************************************************** Wednesday, May 14, 2003 8:00 - 9:00 Breakfast and registration 9:00 - 9:10 Opening remarks Fred Roberts, Director of DIMACS 9:10 - 9:20 Yehuda Vardi Department of Statistics, Rutgers University 9:20 - 9:40 Marianthi Markatou Program Director, NSF Statistics Program Chair: Arthur Cohen 9:40 - 10:40 An Overview on Depth Functions in Nonparametric Multivariate Analysis Robert Serfling, University of Texas at Dallas 10:40 - 11:00 Short Break Chair: Diane Souvaine 11:00 - 12:00 Depth and Arrangements David Eppstein, University of California, Irvine 12:00 - 1:30 Lunch Chair: Xuming He 1:30 - 2:10 Data Analysis by Zonoid Depth Karl Mosler, Universitat zu Koln, Germany 2:10 - 2:50 Data Depth in Multivariate Analysis: Dependence, Discrimination and Clustering Mario Romanazzi, "Ca' Foscari University of Venice, Italy 2:50 - 3:10 Fast Algorithms for Frames and Point Depth in Polyhedral Hulls Jose Dula, University of Mississippi and the U.S. Census Bureau 3:10 - 3:40 Break Chair: David Madigan 3:40 - 4:20 Maximal Depth Estimators of Regression Quantiles for Censored Data Steve Portnoy, University of Illinois 4:20 - 5:00 Data Depth and Mixture Models Ryan Elmore, Thomas Hettmansperger*, Fengjuan Xuan Penn State University 5:00 - 5:40 Comparing Multivariate Scale Using Data Depth: Testing for Expansion or Contraction Kesar Singh, Rutgers University 5:40 - 6:00 A Test for Equal Variances Using Data Depth Karen McGaughey, Kansas State University 6:00 - 7:00 RECEPTION (Wine and Cheese) Thursday, May 15, 2003 8:30 - 9:00 Breakfast and registration Chair: Marshall Bern 9:00 - 9:40 Real-time Computation of Data Depth Using the Graphics Pipeline Suresh Venkatasubramanian, AT&T Labs- Research 9:40 - 10:20 Computing the Center of Area of a Convex Polygon Pat Morin, Carleton University, Canada 10:20 - 10:40 Distance Problems on points and lines Ovidiu Daescu, Ningfang Mi, University of Texas at Dallas 10:40 - 11:00 Short Break Chair: Cun-Hui Zhang 11:00 - 11:40 Computation of Projection Depth and Related Estimators Yijun Zuo, Michigan State University 11:40 - 12:20 On some Probabilistic Algoritms for Computing Tukey's Half Space Depth Biman Chakraborty*, Probal Chaudhuri 12:20 - 2:00 Lunch Chair: Evarist Gine 2:00 - 2:40 On data based distances between data vectors and between hyperplanes Hannu Oja, University of Jyvaskyla, Finland 2:40 - 3:20 On the Computation and Robustness of Some Data Depth Notions Greg Aloupis, McGill University 3:20 - 4:00 Yehuda Vardi Deep Talk 4:00 - 4:30 Break Chair: David Tyler 4:30 - 4:50 A definition of depth for functional observations Sara L?pez-Pintado, Juan Romo* Universidad Carlos III de Madrid, Spain 4:50 - 5:10 A Depth_Based Kurtosis Functional Jin Wang, University of Texas at Dallas 5:10 - 5:50 Tukey depth-based trimmed means Jean-Claude Masse, Universite Laval, Quebec, Canada 6:20 DINNER, DIMACS Lounge Friday, May 16, 2003 8:30 - 9:00 Breakfast and registration Chair: William Steiger 9:00 - 9:40 Clustering and Cluster validation via the Relative Data Depth Rebecka Jornsten, Rutgers University 9:40 - 10:20 On aspects of regression depth and methods based on convex risk minimization for data mining Andreas Christmann, University of Dortmund, Germany 10:20 - 10:40 Short Break Chair: Suneeta Ramaswami 10:40 - 11:20 Nonparametric clustering of high-dimensional data Bogdan Georgescu, Rutgers University Ilan Shimshoni, Technion-Israel Institute of Technology, Israel Peter Meer*, Rutgers University 11:20 - 11:40 Functional Samples and Bootstrap for Predicting SO_2 Levels Belen Fernandez-de-Castro*, S.Guillas, W. Gonzalez Manteiga Universidade de Santiago de Compostela, Spain 11:40 - 12:00 Exact, Adaptive, Parallel Algorithms for Data Depth Problems Vera Rosta, McGill University, Canada 12:00 - 1:20 Lunch Chair: Peter Rousseeuw 1:20 - 2:00 Analyzing The Number of Samples Required for an Approximate Monte-Carlo LMS Line Estimator David M. Mount, University of Maryland 2:00 - 2:40 Optimizing Depth Functions Stefan Langerman, Universite Libre de Bruxelles , 2:40 - 3:00 Short Break Chair: Peter Rousseeuw 3:00 - 3:40 A note on Simplicial Depth & Software Demonstration Michael Burr*, Eynat Rafalin*, Diane Souvaine, Tufts University 3:40 - 5:00 Open Discussion 5:00 Workshop adjourn ****************************************************** Registration Fees: (Pre-registration deadline: May 7, 2003) Regular rate Preregister before deadline $100/day After preregistration deadline $120/day Reduced Rate* Preregister before deadline $50/day After preregistration deadline $60/day Postdocs Preregister before deadline $10/day After preregistration deadline $15/day DIMACS Postdocs $0 Non-Local Graduate & Undergraduate students Preregister before deadline $5/day After preregistration deadline $10/day Local Graduate & Undergraduate students $0 (Rutgers & Princeton) DIMACS partner institution employees** $0 DIMACS long-term visitors*** $0 Registration fee to be collected on site, cash, check, VISA/Mastercard accepted. Our funding agencies require that we charge a registration fee for the workshop. Registration fees cover participation in the workshop, all workshop materials, breakfast, lunch, breaks, and any scheduled social events (if applicable). * College/University faculty and employees of non-profit organizations will automatically receive the reduced rate. Other participants may apply for a reduction of fees. They should email their request for the reduced fee to the Workshop Coordinator at workshop at dimacs.rutgers.edu. Include your name, the Institution you work for, your job title and a brief explanation of your situation. All requests for reduced rates must be received before the preregistration deadline. You will promptly be notified as to the decision about it. ** Fees for employees of DIMACS partner institutions are waived. DIMACS partner institutions are: Rutgers University, Princeton University, AT&T Labs - Research, Bell Labs, NEC Laboratories America and Telcordia Technologies. Fees for employees of DIMACS affiliate members Avaya Labs, IBM Research and Microsoft Research are also waived. ***DIMACS long-term visitors who are in residence at DIMACS for two or more weeks inclusive of dates of workshop. *************************************************************** Information on participation, registration, accommodations, and travel can be found at: http://dimacs.rutgers.edu/Workshops/Depth/ **PLEASE BE SURE TO PRE-REGISTER EARLY** *************************************************************** From lindac at dimacs.rutgers.edu Fri May 16 12:08:39 2003 From: lindac at dimacs.rutgers.edu (Linda Casals) Date: Fri, 16 May 2003 12:08:39 -0400 (EDT) Subject: [Sy-cg-global] PROGRAM: DIMACS Workshop on Geometric Optimization Message-ID: <200305161608.MAA00106@dimacs.rutgers.edu> DIMACS Workshop on Geometric Optimization May 19 - 21, 2003 DIMACS Center, CoRE Building, Rutgers University Organizers: Joe Mitchell, SUNY Stony Brook, jsbm at ams.sunysb.edu Pankaj Agarwal, Duke University, pankaj at cs.duke.edu Presented under the auspices of the Special Focus on Computational Geometry and Applications. **************************************************************** Combinatorial optimization typically deals with problems of maximizing or minimizing a function of one or more variables subject to a large number of constraints. In many applications, the underlying optimization problem involves a constant number of variables and a large number of constraints that are induced by a given collection of geometric objects; these problems are referred to as geometric-optimization problems. Typical examples include facility location, low-dimensional clustering, network-design, optimal path-planning, shape-matching, proximity, and statistical-measure problems. In such cases one expects that faster and simpler algorithms can be developed by exploiting the geometric nature of the problem. Much work has been done on geometric-optimization problems during the last twenty-five years. Many elegant and sophisticated techniques have been proposed and successfully applied to a wide range of geometric-optimization problems. Several randomization and approximation techniques have been proposed. In parallel with the effort in the geometric algorithms community, the mathematical programming and combinatorial optimization communities have made numerous fundamental advances in optimization, both in computation and in theory, during the last quarter century. Interior-point methods, polyhedral combinatorics, and semidefinite programming have been developed as powerful mathematical and computational tools for optimization, and some of them have been used for geometric problems. Scope and Format: This workshop aims to bring together people from different research communities interested in geometric-optimization problems. The goal is to discuss various techniques developed for geometric optimization and their applications, to identify key research issues that need to be addressed, and to help establish relationships which can be used to strengthen and foster collaboration across the different areas. **************************************************************** PROGRAM Monday, May 19, 2003 8:15 - 8:55 Breakfast and Registration 8:55 - 9:00 Opening remarks: Melvin Janowitz, Associate Director of DIMACS 9:00 - 10:00 Unique Sink Orientations of Cubes and its Relations to Optimization Emo Welzl, ETH Zurich 10:00 - 10:30 Smoothed Analysis of Algorithms: Simplex Algorithm and Numerical Analysis Shanghua Teng, Boston University 10:30 - 11:00 Break 11:00 - 11:30 The Protein Side-Chain Positioning Problem Carl Kingsford, Princeton University 11:30 - 12:00 Approximate Protein Structural Alignment in Polynomial Time Rachel Kolodny, Stanford University 12:00 - 12:30 Hausdorff Distance under Translation for Points and Balls Yusu Wang, Duke University 12:30 - 2:00 Lunch 2:00 - 3:00 Emerging Trends in Optimization Dan Bienstock, Columbia University 3:00 - 3:30 Exact Parallel Algorithm for Computing Maximum Feasible Subsystems of Linear Relations Vera Rosta, McGill University 3:30 - 4:00 Improved Embeddings of Metrics into Trees Satish Rao, UC Berkeley 4:00 - 4:30 Break 4:30 - 5:00 Online Searching with Turn Cost Erik Demaine, MIT 5:00 - 5:30 Leave no Stones Unturned: Improved Approximation Algorithms for Degree-Bounded Minimum Spanning Trees Raja Jothi, UT Dallas 5:30 - 6:00 Constructing Spanners of Different Flavors Joachim Gudmundsson Tuesday, May 20, 2003 8:30 - 9:00 Breakfast and registration 9:00 - 10:00 Random Walks and Geometric Algorithms Santosh Vempala, MIT 10:00 - 10:30 Approximation Algorithms for k-Center Clustering Piyush Kumar, SUNY Sony Brook 10:30 - 11:00 Break 11:00 - 11:30 Computing Projective Clusters via Certificates Cecilia M. Procopiuc, AT&T Labs 11:30 - 12:00 Shape Fitting with Outliers Sariel Har-Peled, UIUC 12:00 - 12:30 Approximate Minimum Volume Enclosing Ellipsoids Using Core Sets Alper Yildirim, SUNY Sony Brook 12:30 - 2:00 Lunch 2:00 - 3:00 Geometric Optimization and Arrangements Micha Sharir, Tel Aviv University 3:00 - 3:30 Approximating the k-Radius of High-Dimensional Point Sets Kasturi Varadarajan, University of Iowa 3:30 - 4:00 Break 4:00 - 5:00 Approximation Schemes for Geometric NP-Hard Problems: A Survey Sanjeev Arora, Princeton University 5:00 - 5:30 TSP with Neighborhoods of Varying Size Matthew Katz, Ben Gurion University 5:30 - 6:00 Touring a Sequence of Polygons Alon Efrat, University of Arizona Wednesday, May 21, 2003 8:30 - 9:00 Breakfast and registration 9:00 - 10:00 Quasiconvex Programming David Eppstein, UC Irvine 10:00 - 10:30 Engineering Geometric Optimization Algorithms: Some Experiments Herve Bronnimann, Polytechnic University 10:30 - 11:00 Subtraction in Geometric Searching Bernard Chazelle 11:00 - 11:30 Minimum Separation in Weighted Subdivisions Ovidiu Daescu and James Palmer 11:30 - 12:30 Lunch 12:30 - 1:00 Some Data Streaming Problems in Computational Geometry S. Muthukrishnan, Rutgers University 1:00 - 1:30 Streaming Geometric Optimization Using Graphics Hardware Suresh Venkatasubramanian, AT&T Labs 1:30 - 2:00 Efficient Algorithms for Shared Camera Control Vladlen Koltun, UC Berkeley ************************************************************************* Registration Fees: (Pre-registration deadline: May 12, 2003) Regular rate Preregister before deadline $120/day After preregistration deadline $140/day Reduced Rate* Preregister before deadline $60/day After preregistration deadline $70/day Postdocs Preregister before deadline $10/day After preregistration deadline $15/day DIMACS Postdocs $0 Non-Local Graduate & Undergraduate students Preregister before deadline $5/day After preregistration deadline $10/day Local Graduate & Undergraduate students $0 (Rutgers & Princeton) DIMACS partner institution employees** $0 DIMACS long-term visitors*** $0 Registration fee to be collected on site, cash, check, VISA/Mastercard accepted. Our funding agencies require that we charge a registration fee for the workshop. Registration fees cover participation in the workshop, all workshop materials, breakfast, lunch, breaks, and any scheduled social events (if applicable). * College/University faculty and employees of non-profit organizations will automatically receive the reduced rate. Other participants may apply for a reduction of fees. They should email their request for the reduced fee to the Workshop Coordinator at workshop at dimacs.rutgers.edu. Include your name, the Institution you work for, your job title and a brief explanation of your situation. All requests for reduced rates must be received before the preregistration deadline. You will promptly be notified as to the decision about it. ** Fees for employees of DIMACS partner institutions are waived. DIMACS partner institutions are: Rutgers University, Princeton University, AT&T Labs - Research, Bell Labs, NEC Laboratories America and Telcordia Technologies. Fees for employees of DIMACS affiliate members Avaya Labs, IBM Research and Microsoft Research are also waived. ***DIMACS long-term visitors who are in residence at DIMACS for two or more weeks inclusive of dates of workshop. *************************************************************** Information on participation, registration, accommodations, and travel can be found at: http://dimacs.rutgers.edu/Workshops/GeomOpt/ **PLEASE BE SURE TO PRE-REGISTER EARLY** ***************************************************************