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Mini Symposia & Workshops Mini Symposia & Workshops Mini Symposia & Workshops Sponsored by the Neural Information Processing Systems Foundation, Inc. There are 4 Mini Symposia and 25 workshops covering a rather eclectic range of topics from algebra to neuroscience to computational hardware to photography to behavioral science to bioinformatics to learning theory to internet related problems. They provide an exciting preview for future trends in Neural Information Processing Systems and in this way they com- plement the main conference. Contents Organizing Committee . .7 Program Committee . .7 NIPS Foundation Offices and Board Members . .8 Sponsors . .9 Core Logistics Team . .9 Schedule 11 Workshop Overview 13 MS1 Algebraic methods in machine learning . 17 MS2 Computational Photography . 19 MS3 Machine Learning in Computational Biology . 22 MS4 Principled Theoretical Frameworks for the Perception-Action Cycle . 24 WS1 Beyond Search: Computational Intelligence for the Web . 26 WS2a Speech and Language: Learning-based Methods and Systems . 31 WS2b Speech and Language: Unsupervised Latent-Variable Models . 35 WS3 Statistical Analysis and Modeling of Response Dependencies in Neural Populations . 38 WS4 Algebraic and combinatorial methods in machine learning . 47 WS5 Analyzing Graphs: Theory and Applications . 51 WS6 Machine Learning in Computational Biology . 59 WS7 Machine Learning Meets Human Learning . 61 WS8 Machine Learning Open Source Software . 67 WS9 Optimization for Machine Learning . 72 WS10 Structured Input - Structured Output . 74 WS11 Causality: objectives and assessment . 77 WS12 Cost Sensitive Learning . 79 WS13 New Challenges in Theoretical Machine Learning: Learning with Data-dependent Concept Spaces . 84 WS14 New Directions in Statistical Learning for Meaningful and Reproducible fMRI Analysis . 86 WS15 Cortical Microcircuits and their Computational Functions . 90 WS16 Approximate inference - how far have we come? . 92 WS17 Kernel Learning: Automatic Selection of Optimal Kernels . 94 WS18 Parallel Implementations of Learning Algorithms: What have you done for me lately? . 99 WS19 Model Uncertainty and Risk in Reinforcement Learning . 101 WS20 Principled Theoretical Frameworks for the Perception-Action Cycle . 103 WS21 Probabilistic Programming: Universal Languages and Inference; Systems; and Applications 105 WS22 Stochastic Models of Behaviour . 111 WS23 Learning from Multiple Sources . 115 Index 123 Maps 129 Notes 132 7 Organizing Committee General Chair Daphne Koller, Stanford University Program Co-Chairs Dale Schuurmans, University of Alberta Yoshua Bengio, University of Montreal Tutorial Chair Geoff Gordon, Carnegie Mellon University Workshop Co-Chairs Maneesh Sahani, London College University Alex Smola, Yahoo! Research Demonstration Chair Ralf Herbrich, Microsoft Research Publications Chair Leon Bottou, NEC Labs America Electronic Proceedings Co-Chairs Aron Culotta, Southeastern Louisiana University Andrew McCallum, University of Massachusetts, Amherst Publicity Chair Antonio Torralba, MIT Volunteers Chair Yasemin Altun, Max Planck Institute Program Committee Program Co-Chairs Dale Schuurmans, University of Alberta Yoshua Bengio, University of Montreal Program Committee Area Chairs Jean-Yves Audibert, Ecole Nationale des Ponts et Chauss´ees Francis Bach, INRIA & Ecole Normale Sup´erieure Kristin Bennett, Rensselaer Polytechnic Institute Michael Bowling, University of Alberta Aaron Courville, Universit´ede Montr´eal Koby Crammer, University of Pennsylvania Sanjoy Dasgupta, University of California, San Diego Nathaniel Daw, New York University Eleazar Eskin, University of California, Los Angeles David Fleet, University of Toronto Paolo Frasconi, Universit`adi Firenze Arthur Gretton, Max Planck Institute Tony Jebara, Columbia University Chris Manning, Stanford University Ron Meir, Technion Noboru Murata, Waseda University Erkki Oja, Helsinki University of Technology Doina Precup, McGill University Stefan Schaal, University of Southern California Fei Sha, University of Southern California Alan Stocker, New York University Ingo Steinwart, Los Alamos National Laboratory Erik Sudderth, University of California, Berkeley Yee-Whye Teh, University College London Antonio Torralba, Massachusetts Institute of Technology Larry Wasserman, Carnegie Mellon University Max Welling, University of California, Irvine 8 NIPS Foundation Officers and Board Members President Terrence Sejnowski, The Salk Institute Vice President for Development Sebastian Thrun, Stanford University Treasurer Marian Stewart Bartlett, University of California, San Diego Secretary Michael Mozer, University of Colorado, Boulder Legal Advisor Phil Sotel, Pasadena, CA Executive Board Sue Becker, McMaster University, Ontario, Canada Thomas G. Dietterich, Oregon State University John C. Platt, Microsoft Research Lawrence Saul, University of Pennsylvania Bernhard Scholkopf¨ , Max Planck Institute Sara A. Solla, Northwestern University Medical School Yair Weiss, Hebrew University of Jerusalem Advisory Board Gary Blasdel, Harvard Medical School Jack Cowan, University of Chicago Stephen Hanson, Rutgers University Michael I. Jordan, University of California, Berkeley Michael Kearns, University of Pennsylvania Scott Kirkpatrick, Hebrew University, Jerusalem Richard Lippmann, Massachusetts Institute of Technology Todd K. Leen, Oregon Graduate Institute Bartlett Mel, University of Southern California John Moody, International Computer Science Institute, Berkeley and Portland Gerald Tesauro, IBM Watson Labs Dave Touretzky, Carnegie Mellon University Emeritus Members Terrence L. Fine, Cornell University Eve Marder, Brandeis University 9 Sponsors NIPS gratefully acknowledges the generosity of those individuals and organizations who have provided financial support for the NIPS 2008 conference. The financial support enabled us to sponsor student travel and participation, the outstanding student paper awards, the mini symposia, the demonstration track and the opening buffet. We gratefully acknowledge Yahoo's support in sponsoring the mini- symposia. Microsoft Google Pascal Yahoo Intel Boeing IBM Willow Garage D.E. Shaw Numenta Toyota Research Springer Core Logistics Team The running of NIPS would not be possible without the help of many volunteers, students, researchers and administrators who donate their valuable time and energy to assist the conference in various ways. However, there is a core team at the Salk Institute whose tireless efforts make the conference run smoothly and efficiently every year. This year, NIPS would particularly like to acknowlege the excep- tional work of: Nelson Loyola, Workflow Master Lee Campbell Chris Hiestand Sheri Leone Mary Ellen Perry 10 SCHEDULE 11 Schedule Thursday, December 11th 13.30-16.30 Mini Symposia . Hyatt Vancouver 14.00-18.00 Buses depart Vancouver Hyatt for Westin Resort and Spa 19.00-22.00 Lift Ticket Sales . Westin lobby 17.00-20.30 Registration . Westin Emerald foyer Friday, December 12th 6.30{8.00 Breakfast . Westin Emerald 7.00-11.00 Registration . Westin Emerald foyer 7.30{11.30 Workshop sessions . Westin and Hilton 8.00{9.30 Lift Ticket Sales . Westin lobby 14.30{18.30 Workshop sessions continue . Westin and Hilton Saturday, December 13th 6.30{8.45 Breakfast . Westin Emerald 7.00-11.00 Registration . Westin Emerald foyer 7.30-11.30 Workshop sessions . Westin and Hilton 14.30{18.30 Workshop sessions continue . Westin and Hilton 19.30 { 22.30 Banquet and wrap up meeting . Westin Emerald Some workshops run on different schedules. Please check timings on the subsequent pages. WORKSHOP OVERVIEW 13 Workshop Overview Thursday, December 11th Algebraic methods in machine learning 13.30{16.30 . Regency A/B MS1 Computational Photography 13.30{16.30 . Regency C MS2 Machine Learning in Computational Biology 13:30{16:30 . Regency D MS3 Principled Theoretical Frameworksfor the Perception-Action Cycle 13.30{16.30 . Regency E/F MS4 14 WORKSHOP OVERVIEW Friday, December 12th Beyond Search: Computational Intelligence for the Web 07:30{10:30 and 15:30{18:30 . Westin: Emerald A WS1 Speech and Language: Learning-based Methods and Systems 07:30{10:40 and 15:30{18:30 . Hilton: Cheakamus WS2a Statistical Analysis and Modeling of Response Dependencies in Neural Populations 07:30{10:30 and 15:30{18:30 . Hilton: Mt. Currie N WS3 Algebraic and combinatorial methods in machine learning 07:30{10:30 and 15:30{18:30 . Westin: Callaghan WS4 Analyzing Graphs: Theory and Applications 07:30{10:30 and 15:30{18:30 . Westin: Alpine AB WS5 Machine Learning in Computational Biology 07:45{10:30 and 15:45{18:30 . Hilton: Mt. Currie S WS6 Machine Learning Meets Human Learning 07:30{10:40 and 15:30{18:40 . Hilton: Black Tusk WS7 Machine Learning Open Source Software 07:30{10:30 and 15:30{18:30 . Westin: Alpine CD WS8 Optimization for Machine Learning 07:30{10:30 and 15:30{18:30 . Hilton: Diamond Head WS9 Structured Input - Structured Output 07:30{10:30 and 15:30{18:30 . Hilton: Sutcliffe B WS10 Causality: objectives and assessment 07:30{10:30 and 16:00{19:00 . Westin: Nordic WS11 Cost Sensitive Learning 07:30{10:30 and 16:00{19:00 . Westin: Alpine E WS12 New Challenges in Theoretical Machine Learning: Learning with Data-dependent Concept Spaces 07:30{10:30 and 15:30{18:30 . Hilton: Sutcliffe A WS13 WORKSHOP OVERVIEW 15 Saturday, December 13th Beyond Search: Computational Intelligence for the Web 07:30{10:30 and 15:30{18:30 . Westin: Emerald A WS1 Speech and Language: Unsupervised Latent-Variable Models 07:30{10:30 and 15:30{18:30 . ..
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