MLO - Machine Learning and Optimization Laboratory

Latest additions

• 2017-07-27
  18:11
  P. Kaiser, J. D. Wegner, A. Lucchi, M. Jaggi and T. Hofmann et al. Learning Aerial Image Segmentation from Online Maps, in IEEE Transactions on Geoscience and Remote Sensing, 2017.

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• 2017-07-13
  11:53
  S. U. Stich, A. Raj and M. Jaggi. Approximate Steepest Coordinate Descent. International Conference on Machine Learning (ICML 2017), Sydney, Australia, Aug 6-11, 2017.

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• 2017-07-11
  20:23
  T. Tina Fang, M. Jaggi and K. Argyraki. Generating Steganographic Text with LSTMs. ACL Student Research Workshop 2017, Vancouver, Canada, July 30-August 4, 2017.

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• 2017-06-21
  13:50
  M. Jaggi. Sparse convex optimization methods for machine learning.

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• 2017-06-21
  13:50
  B. Gärtner, J. Giesen, M. Jaggi and T. Welsch. A Combinatorial Algorithm to Compute Regularization Paths, 2009.

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• 2017-06-21
  13:50
  B. Gärtner and M. Jaggi. Coresets for polytope distance. Symposium on Computational Geometry 2009, Aarhus, Denmark, June 8-10, 2009.

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• 2017-06-21
  13:50
  M. Jaggi and M. Sulovský. A Simple Algorithm for Nuclear Norm Regularized Problems. International Conference on Machine Learning (ICML) 2010, Haifa, Israel, June 21-24, 2010.

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• 2017-06-21
  13:50
  J. Giesen, M. Jaggi and S. Laue. Approximating Parameterized Convex Optimization Problems. European Symposia on Algorithms (ESA) 2010, Liverpool, UK, September 6-8, 2010.

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• 2017-06-21
  13:50
  M. Jaggi. Convex Optimization without Projection Steps, 2011.

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• 2017-06-21
  13:50
  J. Giesen, M. Jaggi and S. Laue. Regularization Paths with Guarantees for Convex Semidefinite Optimization. International Conference on Artificial Intelligence and Statistics (AISTATS) 2012, La Palma, Canary Islands, April 21-23, 2012.

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