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Manfred K. Warmuth: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, Manfred K. Warmuth
    Learnability and the Vapnik-Chervonenkis dimension. [Citation Graph (6, 0)][DBLP]
    J. ACM, 1989, v:36, n:4, pp:929-965 [Journal]
  2. Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, Manfred K. Warmuth
    Occam's Razor. [Citation Graph (1, 0)][DBLP]
    Inf. Process. Lett., 1987, v:24, n:6, pp:377-380 [Journal]
  3. Hagit Attiya, Marc Snir, Manfred K. Warmuth
    Computing on an anonymous ring. [Citation Graph (1, 0)][DBLP]
    J. ACM, 1988, v:35, n:4, pp:845-875 [Journal]
  4. Daniel Ratner, Manfred K. Warmuth
    Finding a Shortest Solution for the N × N Extension of the 15-PUZZLE Is Intractable. [Citation Graph (0, 0)][DBLP]
    AAAI, 1986, pp:168-172 [Conf]
  5. Manfred K. Warmuth
    Towards Representation Independence in PAC Learning. [Citation Graph (0, 0)][DBLP]
    AII, 1989, pp:78-103 [Conf]
  6. Eiji Takimoto, Manfred K. Warmuth
    The Last-Step Minimax Algorithm. [Citation Graph (0, 0)][DBLP]
    ALT, 2000, pp:279-290 [Conf]
  7. Eiji Takimoto, Manfred K. Warmuth
    Predicting Nearly as well as the best Pruning of a Planar Decision Graph. [Citation Graph (0, 0)][DBLP]
    ATL, 1999, pp:335-346 [Conf]
  8. Elias Dahlhaus, Manfred K. Warmuth
    Membership for Growing Context Sensitive Grammars is Polynomial. [Citation Graph (0, 0)][DBLP]
    CAAP, 1986, pp:85-99 [Conf]
  9. Leonard Pitt, Manfred K. Warmuth
    The Minimum Consistent DFA Problem Cannot be Approximated within any Polynomial (abstract). [Citation Graph (0, 0)][DBLP]
    Structure in Complexity Theory Conference, 1989, pp:230- [Conf]
  10. Olivier Bousquet, Manfred K. Warmuth
    Tracking a Small Set of Experts by Mixing Past Posteriors. [Citation Graph (0, 0)][DBLP]
    COLT/EuroCOLT, 2001, pp:31-47 [Conf]
  11. Naoki Abe, Manfred K. Warmuth
    On the Computational Complexity of Approximating Distributions by Probabilistic Automata. [Citation Graph (0, 0)][DBLP]
    COLT, 1990, pp:52-66 [Conf]
  12. Naoki Abe, Manfred K. Warmuth, Jun-ichi Takeuchi
    Polynomial Learnability of Probabilistic Concepts with Respect to the Kullback-Leibler Divergence. [Citation Graph (0, 0)][DBLP]
    COLT, 1991, pp:277-289 [Conf]
  13. Jacob Abernethy, John Langford, Manfred K. Warmuth
    Continuous Experts and the Binning Algorithm. [Citation Graph (0, 0)][DBLP]
    COLT, 2006, pp:544-558 [Conf]
  14. Nicolò Cesa-Bianchi, Philip M. Long, Manfred K. Warmuth
    Worst-Case Quadratic Loss Bounds for a Generalization of the Widrow-Hoff Rule. [Citation Graph (0, 0)][DBLP]
    COLT, 1993, pp:429-438 [Conf]
  15. Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth
    Learning of Depth Two Neural Networks with Constant Fan-In at the Hidden Nodes (Extended Abstract). [Citation Graph (0, 0)][DBLP]
    COLT, 1996, pp:333-343 [Conf]
  16. Jürgen Forster, Manfred K. Warmuth
    Relative Expected Instantaneous Loss Bounds. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:90-99 [Conf]
  17. Sally A. Goldman, Manfred K. Warmuth
    Learning Binary Relations Using Weighted Majority Voting. [Citation Graph (0, 0)][DBLP]
    COLT, 1993, pp:453-462 [Conf]
  18. David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth
    Equivalence of Models for Polynomial Learnability. [Citation Graph (0, 0)][DBLP]
    COLT, 1988, pp:42-55 [Conf]
  19. David Haussler, Nick Littlestone, Manfred K. Warmuth
    Predicting {0, 1}-Functions on Randomly Drawn Points. [Citation Graph (0, 0)][DBLP]
    COLT, 1988, pp:280-296 [Conf]
  20. David P. Helmbold, Yoram Singer, Robert E. Schapire, Manfred K. Warmuth
    A Comparison of New and Old Algorithms for a Mixture Estimation Problem. [Citation Graph (0, 0)][DBLP]
    COLT, 1995, pp:69-78 [Conf]
  21. David P. Helmbold, Robert H. Sloan, Manfred K. Warmuth
    Learning Nested Differences of Intersection-Closed Concept Classes. [Citation Graph (0, 0)][DBLP]
    COLT, 1989, pp:41-56 [Conf]
  22. David P. Helmbold, Robert H. Sloan, Manfred K. Warmuth
    Learning Integer Lattices. [Citation Graph (0, 0)][DBLP]
    COLT, 1990, pp:288-302 [Conf]
  23. David P. Helmbold, Manfred K. Warmuth
    Some Weak Learning Results. [Citation Graph (0, 0)][DBLP]
    COLT, 1992, pp:399-412 [Conf]
  24. Mark Herbster, Manfred K. Warmuth
    Tracking the Best Regressor. [Citation Graph (0, 0)][DBLP]
    COLT, 1998, pp:24-31 [Conf]
  25. Jyrki Kivinen, Manfred K. Warmuth
    The Perceptron Algorithm vs. Winnow: Linear vs. Logarithmic Mistake Bounds when few Input Variables are Relevant. [Citation Graph (0, 0)][DBLP]
    COLT, 1995, pp:289-296 [Conf]
  26. Jyrki Kivinen, Manfred K. Warmuth
    Boosting as Entropy Projection. [Citation Graph (0, 0)][DBLP]
    COLT, 1999, pp:134-144 [Conf]
  27. Dima Kuzmin, Manfred K. Warmuth
    Unlabeled Compression Schemes for Maximum Classes, . [Citation Graph (0, 0)][DBLP]
    COLT, 2005, pp:591-605 [Conf]
  28. Dima Kuzmin, Manfred K. Warmuth
    Optimum Follow the Leader Algorithm. [Citation Graph (0, 0)][DBLP]
    COLT, 2005, pp:684-686 [Conf]
  29. Philip M. Long, Manfred K. Warmuth
    Composite Geometric Concepts and Polynomial Predictability. [Citation Graph (0, 0)][DBLP]
    COLT, 1990, pp:273-287 [Conf]
  30. Gunnar Rätsch, Manfred K. Warmuth
    Maximizing the Margin with Boosting. [Citation Graph (0, 0)][DBLP]
    COLT, 2002, pp:334-350 [Conf]
  31. Gunnar Rätsch, Manfred K. Warmuth, Sebastian Mika, Takashi Onoda, Steven Lemm, Klaus-Robert Müller
    Barrier Boosting. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:170-179 [Conf]
  32. Eiji Takimoto, Manfred K. Warmuth
    The Minimax Strategy for Gaussian Density Estimation. pp. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:100-106 [Conf]
  33. Eiji Takimoto, Manfred K. Warmuth
    Path Kernels and Multiplicative Updates. [Citation Graph (0, 0)][DBLP]
    COLT, 2002, pp:74-89 [Conf]
  34. Manfred K. Warmuth
    Compressing to VC Dimension Many Points. [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:743-744 [Conf]
  35. Manfred K. Warmuth
    The Optimal PAC Algorithm. [Citation Graph (0, 0)][DBLP]
    COLT, 2004, pp:641-642 [Conf]
  36. Manfred K. Warmuth
    Can Entropic Regularization Be Replaced by Squared Euclidean Distance Plus Additional Linear Constraints. [Citation Graph (0, 0)][DBLP]
    COLT, 2006, pp:653-654 [Conf]
  37. Manfred K. Warmuth, Dima Kuzmin
    Online Variance Minimization. [Citation Graph (0, 0)][DBLP]
    COLT, 2006, pp:514-528 [Conf]
  38. Manfred K. Warmuth, S. V. N. Vishwanathan
    Leaving the Span. [Citation Graph (0, 0)][DBLP]
    COLT, 2005, pp:366-381 [Conf]
  39. Manfred K. Warmuth
    Sample Compression, Learnability, and the Vapnik-Chervonenkis Dimension. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1997, pp:1-2 [Conf]
  40. David Haussler, Jyrki Kivinen, Manfred K. Warmuth
    Tight worst-case loss bounds for predicting with expert advice. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1995, pp:69-83 [Conf]
  41. David P. Helmbold, Sandra Panizza, Manfred K. Warmuth
    Direct and Indirect Algorithms for On-line Learning of Disjunctions. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1999, pp:138-152 [Conf]
  42. Jyrki Kivinen, Manfred K. Warmuth
    Averaging Expert Predictions [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1999, pp:153-167 [Conf]
  43. Hans L. Bodlaender, Shlomo Moran, Manfred K. Warmuth
    The Distributed Bit Complexity of the Ring: From the Anonymous to the Non-anonymous Case. [Citation Graph (0, 0)][DBLP]
    FCT, 1989, pp:58-67 [Conf]
  44. Peter Auer, Manfred K. Warmuth
    Tracking the Best Disjunction. [Citation Graph (0, 0)][DBLP]
    FOCS, 1995, pp:312-321 [Conf]
  45. David Haussler, Nick Littlestone, Manfred K. Warmuth
    Predicting {0,1}-Functions on Randomly Drawn Points (Extended Abstract) [Citation Graph (0, 0)][DBLP]
    FOCS, 1988, pp:100-109 [Conf]
  46. Nick Littlestone, Manfred K. Warmuth
    The Weighted Majority Algorithm [Citation Graph (0, 0)][DBLP]
    FOCS, 1989, pp:256-261 [Conf]
  47. Jürgen Forster, Manfred K. Warmuth
    Relative Loss Bounds for Temporal-Difference Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:295-302 [Conf]
  48. David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
    On-Line Portfolio Selection Using Multiplicative Updates. [Citation Graph (0, 0)][DBLP]
    ICML, 1996, pp:243-251 [Conf]
  49. Mark Herbster, Manfred K. Warmuth
    Tracking the Best Expert. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:286-294 [Conf]
  50. Wolfgang Maass, Manfred K. Warmuth
    Efficient Learning with Virtual Threshold Gates. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:378-386 [Conf]
  51. Robert E. Schapire, Manfred K. Warmuth
    On the Worst-Case Analysis of Temporal-Difference Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:266-274 [Conf]
  52. Manfred K. Warmuth, Jun Liao, Gunnar Rätsch
    Totally corrective boosting algorithms that maximize the margin. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:1001-1008 [Conf]
  53. Peter Auer, Mark Herbster, Manfred K. Warmuth
    Exponentially many local minima for single neurons. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:316-322 [Conf]
  54. Claudio Gentile, Manfred K. Warmuth
    Linear Hinge Loss and Average Margin. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:225-231 [Conf]
  55. Robert B. Gramacy, Manfred K. Warmuth, Scott A. Brandt, Ismail Ari
    Adaptive Caching by Refetching. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:1465-1472 [Conf]
  56. Kohei Hatano, Manfred K. Warmuth
    Boosting versus Covering. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  57. David P. Helmbold, Jyrki Kivinen, Manfred K. Warmuth
    Worst-case Loss Bounds for Single Neurons. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:309-315 [Conf]
  58. Jyrki Kivinen, Manfred K. Warmuth
    Relative Loss Bounds for Multidimensional Regression Problems. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  59. Gunnar Rätsch, Sebastian Mika, Manfred K. Warmuth
    On the Convergence of Leveraging. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:487-494 [Conf]
  60. Yoram Singer, Manfred K. Warmuth
    Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:641-647 [Conf]
  61. Yoram Singer, Manfred K. Warmuth
    Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:578-584 [Conf]
  62. Koji Tsuda, Gunnar Rätsch, Manfred K. Warmuth
    Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  63. Manfred K. Warmuth
    A Bayes Rule for Density Matrices. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  64. Manfred K. Warmuth
    Relative Loss Bounds, the Minimum Relative Entropy Principle, and EM. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  65. Manfred K. Warmuth, Gunnar Rätsch, Michael Mathieson, Jun Liao, Christian Lemmen
    Active Learning in the Drug Discovery Process. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1449-1456 [Conf]
  66. Chagit Attiya, Marc Snir, Manfred K. Warmuth
    Computing on an Anonymous Ring. [Citation Graph (0, 0)][DBLP]
    PODC, 1985, pp:196-203 [Conf]
  67. Shlomo Moran, Manfred K. Warmuth
    Gap Theorems for Distributed Computation. [Citation Graph (0, 0)][DBLP]
    PODC, 1986, pp:131-140 [Conf]
  68. Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, Manfred K. Warmuth
    Classifying Learnable Geometric Concepts with the Vapnik-Chervonenkis Dimension (Extended Abstract) [Citation Graph (0, 0)][DBLP]
    STOC, 1986, pp:273-282 [Conf]
  69. Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, David Haussler, Robert E. Schapire, Manfred K. Warmuth
    How to use expert advice. [Citation Graph (0, 0)][DBLP]
    STOC, 1993, pp:382-391 [Conf]
  70. Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
    Using and Combining Predictors That Specialize. [Citation Graph (0, 0)][DBLP]
    STOC, 1997, pp:334-343 [Conf]
  71. Jyrki Kivinen, Manfred K. Warmuth
    Additive versus exponentiated gradient updates for linear prediction. [Citation Graph (0, 0)][DBLP]
    STOC, 1995, pp:209-218 [Conf]
  72. Nick Littlestone, Philip M. Long, Manfred K. Warmuth
    On-Line Learning of Linear Functions [Citation Graph (0, 0)][DBLP]
    STOC, 1991, pp:465-475 [Conf]
  73. Leonard Pitt, Manfred K. Warmuth
    The Minimum Consistent DFA Problem Cannot Be Approximated within any Polynomial [Citation Graph (0, 0)][DBLP]
    STOC, 1989, pp:421-432 [Conf]
  74. Katy S. Azoury, Manfred K. Warmuth
    Relative Loss Bounds for On-line Density Estirnation with the Exponential Family of Distributions. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:31-40 [Conf]
  75. Jakob Gonczarowski, Manfred K. Warmuth
    Scattered Versus Context-Sensitive Rewriting. [Citation Graph (0, 0)][DBLP]
    Acta Inf., 1989, v:27, n:1, pp:81-95 [Journal]
  76. Jyrki Kivinen, Manfred K. Warmuth, Peter Auer
    The Perceptron Algorithm Versus Winnow: Linear Versus Logarithmic Mistake Bounds when Few Input Variables are Relevant (Technical Note). [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1997, v:97, n:1-2, pp:325-343 [Journal]
  77. Nick Littlestone, Philip M. Long, Manfred K. Warmuth
    On-line Learning of Linear Functions. [Citation Graph (0, 0)][DBLP]
    Computational Complexity, 1995, v:5, n:1, pp:1-23 [Journal]
  78. Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth
    Learning of Depth Two Neural Networks with Constant Fan-in at the Hidden Nodes [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:55, pp:- [Journal]
  79. Peter Auer, Manfred K. Warmuth
    Tracking the best disjunction [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:70, pp:- [Journal]
  80. Richard J. Anderson, Ernst W. Mayr, Manfred K. Warmuth
    Parallel Approximation Algorithms for Bin Packing [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1989, v:82, n:3, pp:262-277 [Journal]
  81. Hans L. Bodlaender, Shlomo Moran, Manfred K. Warmuth
    The Distributed Bit Complexity of the Ring: From the Anonymous to the Non-anonymous Case [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1994, v:108, n:1, pp:34-50 [Journal]
  82. David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth
    Equivalence of Models for Polynomial Learnability [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1991, v:95, n:2, pp:129-161 [Journal]
  83. David Haussler, Nick Littlestone, Manfred K. Warmuth
    Predicting \0,1\-Functions on Randomly Drawn Points [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1994, v:115, n:2, pp:248-292 [Journal]
  84. Jyrki Kivinen, Manfred K. Warmuth
    Exponentiated Gradient Versus Gradient Descent for Linear Predictors. [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1997, v:132, n:1, pp:1-63 [Journal]
  85. Nick Littlestone, Manfred K. Warmuth
    The Weighted Majority Algorithm [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1994, v:108, n:2, pp:212-261 [Journal]
  86. Philip M. Long, Manfred K. Warmuth
    Composite Geometric Concepts and Polynomial Predictability [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1994, v:113, n:2, pp:230-252 [Journal]
  87. Wolfgang Maass, Manfred K. Warmuth
    Efficient Learning With Virtual Threshold Gates. [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1998, v:141, n:1, pp:66-83 [Journal]
  88. Nicolò Cesa-Bianchi, Yoav Freund, David Haussler, David P. Helmbold, Robert E. Schapire, Manfred K. Warmuth
    How to use expert advice. [Citation Graph (0, 0)][DBLP]
    J. ACM, 1997, v:44, n:3, pp:427-485 [Journal]
  89. Leonard Pitt, Manfred K. Warmuth
    The Minimum Consistent DFA Problem Cannot be Approximated within any Polynomial. [Citation Graph (0, 0)][DBLP]
    J. ACM, 1993, v:40, n:1, pp:95-142 [Journal]
  90. Danny Dolev, Manfred K. Warmuth
    Scheduling Precedence Graphs of Bounded Height. [Citation Graph (0, 0)][DBLP]
    J. Algorithms, 1984, v:5, n:1, pp:48-59 [Journal]
  91. Manfred K. Warmuth, Jun Liao, Gunnar Rätsch, Michael Mathieson, Santosh Putta, Christian Lemmen
    Active Learning with Support Vector Machines in the Drug Discovery Process. [Citation Graph (0, 0)][DBLP]
    Journal of Chemical Information and Computer Sciences, 2003, v:43, n:2, pp:667-673 [Journal]
  92. Elias Dahlhaus, Manfred K. Warmuth
    Membership for Growing Context-Sensitive Grammars is Polynomial. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1986, v:33, n:3, pp:456-472 [Journal]
  93. Jürgen Forster, Manfred K. Warmuth
    Relative Expected Instantaneous Loss Bounds. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 2002, v:64, n:1, pp:76-102 [Journal]
  94. David P. Helmbold, Manfred K. Warmuth
    On Weak Learning. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1995, v:50, n:3, pp:551-573 [Journal]
  95. Leonard Pitt, Manfred K. Warmuth
    Prediction-Preserving Reducibility. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1990, v:41, n:3, pp:430-467 [Journal]
  96. Manfred K. Warmuth, David Haussler
    On the Complexity of Iterated Shuffle. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1984, v:28, n:3, pp:345-358 [Journal]
  97. Mark Herbster, Manfred K. Warmuth
    Tracking the Best Linear Predictor. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2001, v:1, n:, pp:281-309 [Journal]
  98. Olivier Bousquet, Manfred K. Warmuth
    Tracking a Small Set of Experts by Mixing Past Posteriors. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:363-396 [Journal]
  99. Eiji Takimoto, Manfred K. Warmuth
    Path Kernels and Multiplicative Updates. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2003, v:4, n:, pp:773-818 [Journal]
  100. Gunnar Rätsch, Manfred K. Warmuth
    Efficient Margin Maximizing with Boosting. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:2131-2152 [Journal]
  101. Koji Tsuda, Gunnar Rätsch, Manfred K. Warmuth
    Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:995-1018 [Journal]
  102. Danny Dolev, Eli Upfal, Manfred K. Warmuth
    The Parallel Complexity of Scheduling with Precedence Constraints. [Citation Graph (0, 0)][DBLP]
    J. Parallel Distrib. Comput., 1986, v:3, n:4, pp:553-576 [Journal]
  103. Daniel Ratner, Manfred K. Warmuth
    NxN Puzzle and Related Relocation Problem. [Citation Graph (0, 0)][DBLP]
    J. Symb. Comput., 1990, v:10, n:2, pp:111-138 [Journal]
  104. Naoki Abe, Manfred K. Warmuth
    On the Computational Complexity of Approximating Distributions by Probabilistic Automata. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1992, v:9, n:, pp:205-260 [Journal]
  105. Peter Auer, Manfred K. Warmuth
    Tracking the Best Disjunction. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:32, n:2, pp:127-150 [Journal]
  106. Katy S. Azoury, Manfred K. Warmuth
    Relative Loss Bounds for On-Line Density Estimation with the Exponential Family of Distributions. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2001, v:43, n:3, pp:211-246 [Journal]
  107. Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, Manfred K. Warmuth
    On-line Prediction and Conversion Strategies. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1996, v:25, n:1, pp:71-110 [Journal]
  108. Sally Floyd, Manfred K. Warmuth
    Sample Compression, Learnability, and the Vapnik-Chervonenkis Dimension. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1995, v:21, n:3, pp:269-304 [Journal]
  109. Jürgen Forster, Manfred K. Warmuth
    Relative Loss Bounds for Temporal-Difference Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2003, v:51, n:1, pp:23-50 [Journal]
  110. Sally A. Goldman, Manfred K. Warmuth
    Learning Binary Relations Using Weighted Majority Voting. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1995, v:20, n:3, pp:245-271 [Journal]
  111. David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
    A Comparison of New and Old Algorithms for a Mixture Estimation Problem. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:27, n:1, pp:97-119 [Journal]
  112. David P. Helmbold, Robert H. Sloan, Manfred K. Warmuth
    Learning Nested Differences of Intersection-Closed Concept Classes. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1990, v:5, n:, pp:165-196 [Journal]
  113. Mark Herbster, Manfred K. Warmuth
    Tracking the Best Expert. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:32, n:2, pp:151-178 [Journal]
  114. Jyrki Kivinen, Manfred K. Warmuth
    Relative Loss Bounds for Multidimensional Regression Problems. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2001, v:45, n:3, pp:301-329 [Journal]
  115. Robert E. Schapire, Manfred K. Warmuth
    On the Worst-Case Analysis of Temporal-Difference Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1996, v:22, n:1-3, pp:95-121 [Journal]
  116. Danny Dolev, Manfred K. Warmuth
    Scheduling Flat Graphs. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 1985, v:14, n:3, pp:638-657 [Journal]
  117. David P. Helmbold, Robert H. Sloan, Manfred K. Warmuth
    Learning Integer Lattices. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 1992, v:21, n:2, pp:240-266 [Journal]
  118. Shlomo Moran, Manfred K. Warmuth
    Gap Theorems for Distributed Computation. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 1993, v:22, n:2, pp:379-394 [Journal]
  119. Barbara B. Simons, Manfred K. Warmuth
    A Fast Algorithm for Multiprocessor Scheduling of Unit-Length Jobs. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 1989, v:18, n:4, pp:690-710 [Journal]
  120. Jakob Gonczarowski, Manfred K. Warmuth
    Applications of Scheduling Theory to Formal Language Theory. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 1985, v:37, n:, pp:217-243 [Journal]
  121. Jakob Gonczarowski, Manfred K. Warmuth
    Manipulating Derivation Forests by Scheduling Techniques. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 1986, v:45, n:1, pp:87-119 [Journal]
  122. David P. Helmbold, Sandra Panizza, Manfred K. Warmuth
    Direct and indirect algorithms for on-line learning of disjunctions. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 2002, v:284, n:1, pp:109-142 [Journal]
  123. Eiji Takimoto, Manfred K. Warmuth
    Predicting nearly as well as the best pruning of a planar decision graph. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 2002, v:288, n:2, pp:217-235 [Journal]
  124. Nicolò Cesa-Bianchi, Anders Krogh, Manfred K. Warmuth
    Bounds on approximate steepest descent for likelihood maximization in exponential families. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1994, v:40, n:4, pp:1215-0 [Journal]
  125. David Haussler, Jyrki Kivinen, Manfred K. Warmuth
    Sequential Prediction of Individual Sequences Under General Loss Functions. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1998, v:44, n:5, pp:1906-1925 [Journal]
  126. David P. Helmbold, Manfred K. Warmuth
    Learning Permutations with Exponential Weights. [Citation Graph (0, 0)][DBLP]
    COLT, 2007, pp:469-483 [Conf]
  127. Manfred K. Warmuth
    When Is There a Free Matrix Lunch? [Citation Graph (0, 0)][DBLP]
    COLT, 2007, pp:630-632 [Conf]
  128. Manfred K. Warmuth
    Winnowing subspaces. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:999-1006 [Conf]
  129. Dima Kuzmin, Manfred K. Warmuth
    Online kernel PCA with entropic matrix updates. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:465-472 [Conf]
  130. Manfred K. Warmuth, Dima Kuzmin
    Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1481-1488 [Conf]
  131. Manfred K. Warmuth
    A Bayesian Probability Calculus for Density Matrices. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  132. Manfred K. Warmuth, Dima Kuzmin
    A Bayesian Probability Calculus for Density Matrices. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]

  133. Entropy Regularized LPBoost. [Citation Graph (, )][DBLP]


  134. The Blessing and the Curse of the Multiplicative Updates. [Citation Graph (, )][DBLP]


  135. When Random Play is Optimal Against an Adversary. [Citation Graph (, )][DBLP]


  136. Learning Rotations. [Citation Graph (, )][DBLP]


  137. Tutorial summary: Survey of boosting from an optimization perspective. [Citation Graph (, )][DBLP]


  138. New combination coefficients for AdaBoost algorithms. [Citation Graph (, )][DBLP]


  139. Boosting Algorithms for Maximizing the Soft Margin. [Citation Graph (, )][DBLP]


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