Lawrence Cayton : papers


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Papers

  • L. Cayton. Accelerating nearest neighbor search on manycore systems. Twenty-Sixth IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2012.
    [pdf, slides (from MASSIVE 2011), code] (see ADMS paper for GPU implementation details)
  • T. Kam-Thong, C-A. Azencott, L. Cayton, B. Pütz, A. Altmann, N. Karbalai, P. Sämann, B. Schölkopf, B. Müller-Myhsok, and K. Borgwardt. GLIDE: GPU-based linear regression for the detection of epistasis. Human Heredity, 2012, 73:220-236.
    [pdf]
  • L. Cayton. A nearest neighbor data structure for graphics hardware. ADMS workshop, 2010.
    [pdf, slides, code]
  • L. Cayton. Efficient bregman range search. Advances in Neural Information Processing Systems 22 (NeurIPS), 2009.
    [pdf]
  • L. Cayton. Fast nearest neighbor retrieval for bregman divergences. Twenty-Fifth International Conference on Machine Learning (ICML), 2008.
    [pdf, slides, code]
  • S. Agarwal, J. Wills, L. Cayton, G. Lanckriet, D. Kriegman, S. Belongie. Generalized non-metric multidimensional scaling. Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS), 2007.
    [pdf]
  • L. Cayton and S. Dasgupta. A learning framework for nearest neighbor search. Advances in Neural Information Processing Systems 20 (NeurIPS), 2007.
    [pdf]
  • L. Cayton and S. Dasgupta. Robust Euclidean embedding. Twenty-Third International Conference on Machine Learning (ICML), 2006.
    [pdf, slides, code]
  • L. Cayton, R. Herring, A. Holder, J. Holzer, C. Nightingale, T. Stohs. Asymptotic sign-solvability, multiple objective linear programming, and the nonsubstitution theorem. Mathematical Methods of Operations Reseach, 64: 541-555, 2006.
    [link]
  • L. Cayton. Algorithms for manifold learning. UCSD tech report CS2008-0923.
    [pdf] (research exam from Spring 2005)