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Peter Auer: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Chamy Allenberg, Peter Auer, László Györfi, György Ottucsák
    Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring. [Citation Graph (0, 0)][DBLP]
    ALT, 2006, pp:229-243 [Conf]
  2. Peter Auer
    Learning Nested Differences in the Presence of Malicious Noise. [Citation Graph (0, 0)][DBLP]
    ALT, 1995, pp:123-137 [Conf]
  3. Peter Auer, Nicolò Cesa-Bianchi
    On-line Learning with Malicious Noise and the Closure Algorithm. [Citation Graph (0, 0)][DBLP]
    AII/ALT, 1994, pp:229-247 [Conf]
  4. Peter Auer
    An Improved On-line Algorithm for Learning Linear Evaluation Functions. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:118-125 [Conf]
  5. Peter Auer
    On-Line Learning of Rectangles in Noisy Environments. [Citation Graph (0, 0)][DBLP]
    COLT, 1993, pp:253-261 [Conf]
  6. Peter Auer, Claudio Gentile
    Adaptive and Self-Confident On-Line Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:107-117 [Conf]
  7. 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]
  8. Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
    On the Complexity of Function Learning. [Citation Graph (0, 0)][DBLP]
    COLT, 1993, pp:392-401 [Conf]
  9. Peter Auer, Ronald Ortner
    A New PAC Bound for Intersection-Closed Concept Classes. [Citation Graph (0, 0)][DBLP]
    COLT, 2004, pp:408-414 [Conf]
  10. Andreas Opelt, Michael Fussenegger, Axel Pinz, Peter Auer
    Weak Hypotheses and Boosting for Generic Object Detection and Recognition. [Citation Graph (0, 0)][DBLP]
    ECCV (2), 2004, pp:71-84 [Conf]
  11. Peter Auer, Ronald Ortner
    A Boosting Approach to Multiple Instance Learning. [Citation Graph (0, 0)][DBLP]
    ECML, 2004, pp:63-74 [Conf]
  12. Peter Auer
    Using Upper Confidence Bounds for Online Learning. [Citation Graph (0, 0)][DBLP]
    FOCS, 2000, pp:270-279 [Conf]
  13. Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire
    Gambling in a Rigged Casino: The Adversarial Multi-Arm Bandit Problem. [Citation Graph (0, 0)][DBLP]
    FOCS, 1995, pp:322-331 [Conf]
  14. Peter Auer, Manfred K. Warmuth
    Tracking the Best Disjunction. [Citation Graph (0, 0)][DBLP]
    FOCS, 1995, pp:312-321 [Conf]
  15. Peter Auer, Harald Burgsteiner, Wolfgang Maass
    Reducing Communication for Distributed Learning in Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:123-128 [Conf]
  16. Peter Auer
    On Learning From Multi-Instance Examples: Empirical Evaluation of a Theoretical Approach. [Citation Graph (0, 0)][DBLP]
    ICML, 1997, pp:21-29 [Conf]
  17. Peter Auer, Robert C. Holte, Wolfgang Maass
    Theory and Applications of Agnostic PAC-Learning with Small Decision Trees. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:21-29 [Conf]
  18. Michael Fussenegger, Andreas Opelt, Axel Pinz, Peter Auer
    Object Recognition Using Segmentation for Feature Detection. [Citation Graph (0, 0)][DBLP]
    ICPR (3), 2004, pp:41-44 [Conf]
  19. Peter Auer
    Solving String Equations with Constant Restrictions. [Citation Graph (0, 0)][DBLP]
    IWWERT, 1991, pp:103-132 [Conf]
  20. Peter Auer
    Unification in the Combination of Disjoint Theories. [Citation Graph (0, 0)][DBLP]
    IWWERT, 1991, pp:177-186 [Conf]
  21. 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]
  22. Peter Auer, Pasquale Caianiello, Nicolò Cesa-Bianchi
    Tight Bounds on the Cumulative Profit of Distributed Voters (Abstract). [Citation Graph (0, 0)][DBLP]
    PODC, 1996, pp:312- [Conf]
  23. Christian Savu-Krohn, Peter Auer
    A Simple Feature Extraction for High Dimensional Image Representations. [Citation Graph (0, 0)][DBLP]
    SLSFS, 2005, pp:163-172 [Conf]
  24. Peter Auer, Philip M. Long
    Simulating access to hidden information while learning. [Citation Graph (0, 0)][DBLP]
    STOC, 1994, pp:263-272 [Conf]
  25. Peter Auer, Philip M. Long, Aravind Srinivasan
    Approximating Hyper-Rectangles: Learning and Pseudo-Random Sets. [Citation Graph (0, 0)][DBLP]
    STOC, 1997, pp:314-323 [Conf]
  26. Martin Antenreiter, Christian Savu-Krohn, Peter Auer
    Visual Classification of Images by Learning Geometric Appearances Through Boosting. [Citation Graph (0, 0)][DBLP]
    ANNPR, 2006, pp:233-243 [Conf]
  27. 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]
  28. Peter Auer, Nicolò Cesa-Bianchi
    On-Line Learning with Malicious Noise and the Closure Algorithm. [Citation Graph (0, 0)][DBLP]
    Ann. Math. Artif. Intell., 1998, v:23, n:1-2, pp:83-99 [Journal]
  29. Peter Auer
    On-line Learning of Rectangles in Noisy Environments [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:63, pp:- [Journal]
  30. Peter Auer
    On Learning from Ambiguous Information [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:66, pp:- [Journal]
  31. Peter Auer, Philip M. Long
    Simulating Access to Hidden Information while Learning [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:67, pp:- [Journal]
  32. Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire
    Gambling in a rigged casino: The adversarial multi-armed bandit problem [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:68, pp:- [Journal]
  33. Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
    On the Complexity of Function Learning [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:50, pp:- [Journal]
  34. 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]
  35. Peter Auer
    Learning Nested Differences in the Presence of Malicious Noise [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:69, pp:- [Journal]
  36. 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]
  37. Peter Auer, Nicolò Cesa-Bianchi
    On-line Learning with Malicious Noise and the Closure Algorithm [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:71, pp:- [Journal]
  38. Peter Auer, Philip M. Long, Aravind Srinivasan
    Approximating Hyper-Rectangles: Learning and Pseudo-random Sets [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:72, pp:- [Journal]
  39. Keith Andrews, Wolfgang Kienreich, Vedran Sabol, Jutta Becker, Georg Droschl, Frank Kappe, Michael Granitzer, Peter Auer, Klaus Tochtermann
    The InfoSky visual explorer: exploiting hierarchical structure and document similarities. [Citation Graph (0, 0)][DBLP]
    Information Visualization, 2002, v:1, n:3-4, pp:166-181 [Journal]
  40. Peter Auer, Nicolò Cesa-Bianchi, Claudio Gentile
    Adaptive and Self-Confident On-Line Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 2002, v:64, n:1, pp:48-75 [Journal]
  41. Peter Auer, Philip M. Long, Aravind Srinivasan
    Approximating Hyper-Rectangles: Learning and Pseudorandom Sets. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1998, v:57, n:3, pp:376-388 [Journal]
  42. Peter Auer
    Using Confidence Bounds for Exploitation-Exploration Trade-offs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:397-422 [Journal]
  43. Peter Auer, Nicolò Cesa-Bianchi, Paul Fischer
    Finite-time Analysis of the Multiarmed Bandit Problem. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:47, n:2-3, pp:235-256 [Journal]
  44. Peter Auer, Philip M. Long
    Structural Results About On-line Learning Models With and Without Queries. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1999, v:36, n:3, pp:147-181 [Journal]
  45. Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
    On the Complexity of Function Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1995, v:18, n:2-3, pp:187-230 [Journal]
  46. 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]
  47. Andreas Opelt, Axel Pinz, Michael Fussenegger, Peter Auer
    Generic Object Recognition with Boosting. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2006, v:28, n:3, pp:416-431 [Journal]
  48. Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire
    The Nonstochastic Multiarmed Bandit Problem. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 2002, v:32, n:1, pp:48-77 [Journal]
  49. Peter Auer
    Learning Nested Differences in the Presence of Malicious Noise. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 1997, v:185, n:1, pp:159-175 [Journal]
  50. Peter Auer, Ronald Ortner, Csaba Szepesvári
    Improved Rates for the Stochastic Continuum-Armed Bandit Problem. [Citation Graph (0, 0)][DBLP]
    COLT, 2007, pp:454-468 [Conf]
  51. Peter Auer, Ronald Ortner
    Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:49-56 [Conf]
  52. Peter Auer, Ronald Ortner
    A new PAC bound for intersection-closed concept classes. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2007, v:66, n:2-3, pp:151-163 [Journal]

  53. An Efficient Search Algorithm for Content-Based Image Retrieval with User Feedback. [Citation Graph (, )][DBLP]


  54. Workshop summary: On-line learning with limited feedback. [Citation Graph (, )][DBLP]


  55. Consistent Interpretation of Image Sequences to Improve Object Models on the Fly. [Citation Graph (, )][DBLP]


  56. Near-optimal Regret Bounds for Reinforcement Learning. [Citation Graph (, )][DBLP]


  57. Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval. [Citation Graph (, )][DBLP]


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