Peter Auer

Shiau Hong Lim, Peter Auer: Autonomous Exploration For Navigating In MDPs. Journal of Machine Learning Research - Proceedings Track 23: 40.1-40.24 (2012)

Yevgeny Seldin, Nicolò Cesa-Bianchi, Peter Auer, François Laviolette, John Shawe-Taylor: PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits. Journal of Machine Learning Research - Proceedings Track 26: 98-111 (2012)

Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor, Peter Auer: PAC-Bayesian Inequalities for Martingales. IEEE Transactions on Information Theory 58(12): 7086-7093 (2012)

Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos: Regret Bounds for Restless Markov Bandits. ALT 2012: 214-228

Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, Peter Stone: PAC Subset Selection in Stochastic Multi-armed Bandits. ICML 2012

Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor, Peter Auer: PAC-Bayesian Inequalities for Martingales. UAI 2012: 12

Shiau Hong Lim, Peter Auer: Noisy Search with Comparative Feedback. CoRR abs/1202.3741 (2012)

Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos: Regret Bounds for Restless Markov Bandits. CoRR abs/1209.2693 (2012)

Peter Auer, Shiau Hong Lim, Chris Watkins: Models for Autonomously Motivated Exploration in Reinforcement Learning - (Extended Abstract). ALT 2011: 14-17

Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Peter Auer: Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits. ALT 2011: 189-203

Peter Auer, Shiau Hong Lim, Chris Watkins: Models for Autonomously Motivated Exploration in Reinforcement Learning. Discovery Science 2011: 29

Peter Auer: Invited Talk: UCRL and Autonomous Exploration. EWRL 2011: 1

Peter Auer: Exploration and Exploitation in Online Learning. ICAIS 2011: 2

Yevgeny Seldin, Peter Auer, François Laviolette, John Shawe-Taylor, Ronald Ortner: PAC-Bayesian Analysis of Contextual Bandits. NIPS 2011: 1683-1691

Shiau Hong Lim, Peter Auer: Noisy Search with Comparative Feedback. UAI 2011: 445-452

Yevgeny Seldin, François Laviolette, John Shawe-Taylor, Jan Peters, Peter Auer: PAC-Bayesian Analysis of Martingales and Multiarmed Bandits. CoRR abs/1105.2416 (2011)

Yevgeny Seldin, Nicolò Cesa-Bianchi, François Laviolette, Peter Auer, John Shawe-Taylor, Jan Peters: PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off. CoRR abs/1105.4585 (2011)

Yevgeny Seldin, Nicolò Cesa-Bianchi, Peter Auer, François Laviolette, John Shawe-Taylor: PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits. CoRR abs/1110.6755 (2011)

Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor, Peter Auer: PAC-Bayesian Inequalities for Martingales. CoRR abs/1110.6886 (2011)

Peter Auer, Zakria Hussain, Samuel Kaski, Arto Klami, Jussi Kujala, Jorma Laaksonen, Alex Po Leung, Kitsuchart Pasupa, John Shawe-Taylor: Pinview: Implicit Feedback in Content-Based Image Retrieval. Journal of Machine Learning Research - Proceedings Track 11: 51-57 (2010)

Thomas Jaksch, Ronald Ortner, Peter Auer: Near-optimal Regret Bounds for Reinforcement Learning. Journal of Machine Learning Research 11: 1563-1600 (2010)

Peter Auer, Ronald Ortner: UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem. Periodica Mathematica Hungarica 61(1-2): 55-65 (2010)

Zakria Hussain, Alex Po Leung, Kitsuchart Pasupa, David R. Hardoon, Peter Auer, John Shawe-Taylor: Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval. ECML/PKDD (1) 2010: 554-569

Peter Auer: Online Learning. Encyclopedia of Machine Learning 2010: 736-743

Jean-Yves Audibert, Peter Auer, Alessandro Lazaric, Rémi Munos, Daniil Ryabko, Csaba Szepesvári: Workshop summary: On-line learning with limited feedback. ICML 2009: 168

Johann Prankl, Martin Antenreiter, Peter Auer, Markus Vincze: Consistent Interpretation of Image Sequences to Improve Object Models on the Fly. ICVS 2009: 384-393

Peter Auer, Philip M. Long: Guest editors' introduction: Special issue on learning theory. J. Comput. Syst. Sci. 74(8): 1227 (2008)

Peter Auer, Harald Burgsteiner, Wolfgang Maass: A learning rule for very simple universal approximators consisting of a single layer of perceptrons. Neural Networks 21(5): 786-795 (2008)

Alex Po Leung, Peter Auer: An Efficient Search Algorithm for Content-Based Image Retrieval with User Feedback. ICDM Workshops 2008: 884-890

Peter Auer, Thomas Jaksch, Ronald Ortner: Near-optimal Regret Bounds for Reinforcement Learning. NIPS 2008: 89-96

Peter Auer: Learning with Malicious Noise. Encyclopedia of Algorithms 2008

Peter Auer, Ronald Ortner: A new PAC bound for intersection-closed concept classes. Machine Learning 66(2-3): 151-163 (2007)

Peter Auer, Ronald Ortner, Csaba Szepesvári: Improved Rates for the Stochastic Continuum-Armed Bandit Problem. COLT 2007: 454-468

Peter Auer, Nicolò Cesa-Bianchi: A distributed voting scheme to maximize preferences. ITA 40(2): 389-403 (2006)

Andreas Opelt, Axel Pinz, Michael Fussenegger, Peter Auer: Generic Object Recognition with Boosting. IEEE Trans. Pattern Anal. Mach. Intell. 28(3): 416-431 (2006)

Chamy Allenberg, Peter Auer, László Györfi, György Ottucsák: Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring. ALT 2006: 229-243

Martin Antenreiter, Christian Savu-Krohn, Peter Auer: Visual Classification of Images by Learning Geometric Appearances Through Boosting. ANNPR 2006: 233-243

Peter Auer, Ronald Ortner: Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning. NIPS 2006: 49-56

Christian Savu-Krohn, Peter Auer: A Simple Feature Extraction for High Dimensional Image Representations. SLSFS 2005: 163-172

Peter Auer, Ron Meir (Eds.): Learning Theory, 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005, Proceedings. Lecture Notes in Computer Science 3559, Springer 2005, isbn 3-540-26556-2

Peter Auer, Ronald Ortner: A New PAC Bound for Intersection-Closed Concept Classes. COLT 2004: 408-414

Andreas Opelt, Michael Fussenegger, Axel Pinz, Peter Auer: Weak Hypotheses and Boosting for Generic Object Detection and Recognition. ECCV (2) 2004: 71-84

Peter Auer, Ronald Ortner: A Boosting Approach to Multiple Instance Learning. ECML 2004: 63-74

Michael Fussenegger, Andreas Opelt, Axel Pinz, Peter Auer: Object Recognition Using Segmentation for Feature Detection. ICPR (3) 2004: 41-44

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. Information Visualization 1(3-4): 166-181 (2002)

Peter Auer, Nicolò Cesa-Bianchi, Claudio Gentile: Adaptive and Self-Confident On-Line Learning Algorithms. J. Comput. Syst. Sci. 64(1): 48-75 (2002)

Peter Auer: Using Confidence Bounds for Exploitation-Exploration Trade-offs. Journal of Machine Learning Research 3: 397-422 (2002)

Peter Auer, Nicolò Cesa-Bianchi, Paul Fischer: Finite-time Analysis of the Multiarmed Bandit Problem. Machine Learning 47(2-3): 235-256 (2002)

Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire: The Nonstochastic Multiarmed Bandit Problem. SIAM J. Comput. 32(1): 48-77 (2002)

Peter Auer, Harald Burgsteiner, Wolfgang Maass: Reducing Communication for Distributed Learning in Neural Networks. ICANN 2002: 123-128

Peter Auer, Claudio Gentile: Adaptive and Self-Confident On-Line Learning Algorithms. COLT 2000: 107-117

Peter Auer: An Improved On-line Algorithm for Learning Linear Evaluation Functions. COLT 2000: 118-125

Peter Auer: Using Upper Confidence Bounds for Online Learning. FOCS 2000: 270-279

Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger: On the Complexity of Function Learning. Electronic Colloquium on Computational Complexity (ECCC) 7(50) (2000)

Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth: Learning of Depth Two Neural Networks with Constant Fan-in at the Hidden Nodes. Electronic Colloquium on Computational Complexity (ECCC) 7(55) (2000)

Peter Auer: On-line Learning of Rectangles in Noisy Environments. Electronic Colloquium on Computational Complexity (ECCC) 7(63) (2000)

Peter Auer: On Learning from Ambiguous Information. Electronic Colloquium on Computational Complexity (ECCC) 7(66) (2000)

Peter Auer, Philip M. Long: Simulating Access to Hidden Information while Learning. Electronic Colloquium on Computational Complexity (ECCC) 7(67) (2000)

Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire: Gambling in a rigged casino: The adversarial multi-armed bandit problem. Electronic Colloquium on Computational Complexity (ECCC) 7(68) (2000)

Peter Auer: Learning Nested Differences in the Presence of Malicious Noise. Electronic Colloquium on Computational Complexity (ECCC) 7(69) (2000)

Peter Auer, Manfred K. Warmuth: Tracking the best disjunction. Electronic Colloquium on Computational Complexity (ECCC) 7(70) (2000)

Peter Auer, Nicolò Cesa-Bianchi: On-line Learning with Malicious Noise and the Closure Algorithm. Electronic Colloquium on Computational Complexity (ECCC) 7(71) (2000)

Peter Auer, Philip M. Long, Aravind Srinivasan: Approximating Hyper-Rectangles: Learning and Pseudo-random Sets. Electronic Colloquium on Computational Complexity (ECCC) 7(72) (2000)

Peter Auer, Philip M. Long: Structural Results About On-line Learning Models With and Without Queries. Machine Learning 36(3): 147-181 (1999)

Peter Auer, Nicolò Cesa-Bianchi: On-Line Learning with Malicious Noise and the Closure Algorithm. Ann. Math. Artif. Intell. 23(1-2): 83-99 (1998)

Peter Auer, Philip M. Long, Aravind Srinivasan: Approximating Hyper-Rectangles: Learning and Pseudorandom Sets. J. Comput. Syst. Sci. 57(3): 376-388 (1998)

Peter Auer, Manfred K. Warmuth: Tracking the Best Disjunction. Machine Learning 32(2): 127-150 (1998)

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). Artif. Intell. 97(1-2): 325-343 (1997)

Peter Auer: Learning Nested Differences in the Presence of Malicious Noise. Theor. Comput. Sci. 185(1): 159-175 (1997)

Peter Auer: On Learning From Multi-Instance Examples: Empirical Evaluation of a Theoretical Approach. ICML 1997: 21-29

Peter Auer, Philip M. Long, Aravind Srinivasan: Approximating Hyper-Rectangles: Learning and Pseudo-Random Sets. STOC 1997: 314-323

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). COLT 1996: 333-343

Peter Auer, Pasquale Caianiello, Nicolò Cesa-Bianchi: Tight Bounds on the Cumulative Profit of Distributed Voters (Abstract). PODC 1996: 312

Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger: On the Complexity of Function Learning. Machine Learning 18(2-3): 187-230 (1995)

Peter Auer: Learning Nested Differences in the Presence of Malicious Noise. ALT 1995: 123-137

Peter Auer, Manfred K. Warmuth: Tracking the Best Disjunction. FOCS 1995: 312-321

Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire: Gambling in a Rigged Casino: The Adversarial Multi-Arm Bandit Problem. FOCS 1995: 322-331

Peter Auer, Robert C. Holte, Wolfgang Maass: Theory and Applications of Agnostic PAC-Learning with Small Decision Trees. ICML 1995: 21-29

Peter Auer, Mark Herbster, Manfred K. Warmuth: Exponentially many local minima for single neurons. NIPS 1995: 316-322

Kurt Hornik, Maxwell B. Stinchcombe, Halbert White, Peter Auer: Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives. Neural Computation 6(6): 1262-1275 (1994)

Peter Auer, Nicolò Cesa-Bianchi: On-line Learning with Malicious Noise and the Closure Algorithm. AII/ALT 1994: 229-247

Peter Auer, Philip M. Long: Simulating access to hidden information while learning. STOC 1994: 263-272

Peter Auer: On-Line Learning of Rectangles in Noisy Environments. COLT 1993: 253-261

Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger: On the Complexity of Function Learning. COLT 1993: 392-401

Peter Auer: Solving String Equations with Constant Restrictions. IWWERT 1991: 103-132

Peter Auer: Unification in the Combination of Disjoint Theories. IWWERT 1991: 177-186