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Peter Auer
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2020 – today
- 2023
- [j27]Gyula Abraham, Peter Auer
, György Dósa, Tibor Dulai
, Zsolt Tuza, Agnes Werner-Stark:
The bin covering with delivery problem, extended investigations for the online case. Central Eur. J. Oper. Res. 31(1): 21-47 (2023) - [j26]Anika Terbuch
, Paul O'Leary
, Negin Khalili-Motlagh-Kasmaei
, Peter Auer
, Alexander Zöhrer
, Vincent Winter
:
Detecting Anomalous Multivariate Time-Series via Hybrid Machine Learning. IEEE Trans. Instrum. Meas. 72: 1-11 (2023) - [c57]Pratik Gajane, Peter Auer, Ronald Ortner:
Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms. IJCAI 2023: 3714-3722 - 2022
- [c56]Anika Terbuch
, Paul O'Leary, Peter Auer
:
Hybrid Machine Learning for Anomaly Detection in Industrial Time-Series Measurement Data. I2MTC 2022: 1-6 - 2021
- [j25]Peter Auer
, György Dósa, Tibor Dulai
, Armin Fügenschuh, Peggy Näser, Ronald Ortner
, Agnes Werner-Stark:
A new heuristic and an exact approach for a production planning problem. Central Eur. J. Oper. Res. 29(3): 1079-1113 (2021) - [c55]Phongsathorn Kittiworapanya, Kitsuchart Pasupa, Peter Auer
:
Particle Size Estimation in Mixed Commercial Waste Images Using Deep Learning. IAIT 2021: 31:1-31:5 - [c54]Nut Chukamphaeng, Kitsuchart Pasupa, Martin Antenreiter, Peter Auer
:
Learning to Drive with Deep Reinforcement Learning. KST 2021: 147-152
2010 – 2019
- 2019
- [c53]Peter Auer, Pratik Gajane, Ronald Ortner:
Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes. COLT 2019: 138-158 - [c52]Peter Auer, Yifang Chen, Pratik Gajane, Chung-Wei Lee, Haipeng Luo, Ronald Ortner, Chen-Yu Wei:
Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information. COLT 2019: 159-163 - [c51]Ronald Ortner, Pratik Gajane, Peter Auer:
Variational Regret Bounds for Reinforcement Learning. UAI 2019: 81-90 - [i24]Pratik Gajane, Ronald Ortner, Peter Auer:
Variational Regret Bounds for Reinforcement Learning. CoRR abs/1905.05857 (2019) - [i23]Pratik Gajane, Ronald Ortner, Peter Auer, Csaba Szepesvári:
Autonomous exploration for navigating in non-stationary CMPs. CoRR abs/1910.08446 (2019) - 2018
- [j24]Monireh Dabaghchian
, Amir Alipour-Fanid, Kai Zeng
, Qingsi Wang, Peter Auer
:
Online Learning With Randomized Feedback Graphs for Optimal PUE Attacks in Cognitive Radio Networks. IEEE/ACM Trans. Netw. 26(5): 2268-2281 (2018) - [i22]Pratik Gajane, Ronald Ortner, Peter Auer:
A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions. CoRR abs/1805.10066 (2018) - 2017
- [r4]Peter Auer:
Online Learning. Encyclopedia of Machine Learning and Data Mining 2017: 929-937 - [i21]Monireh Dabaghchian, Amir Alipour-Fanid, Kai Zeng, Qingsi Wang, Peter Auer:
Optimal Online Learning with Randomized Feedback Graphs with Application in PUE Attacks in CRN. CoRR abs/1709.10128 (2017) - 2016
- [j23]Peter Auer
, Alexander Clark, Thomas Zeugmann:
Guest editors' foreword. Theor. Comput. Sci. 650: 1-3 (2016) - [c50]Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina M. Drugan:
Pareto Front Identification from Stochastic Bandit Feedback. AISTATS 2016: 939-947 - [c49]Peter Auer, Chao-Kai Chiang:
An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits. COLT 2016: 116-120 - [r3]Peter Auer:
Learning with Malicious Noise. Encyclopedia of Algorithms 2016: 1086-1089 - [i20]Peter Auer, Chao-Kai Chiang:
An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits. CoRR abs/1605.08722 (2016) - 2015
- [i19]Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Peter Auer, András Antos:
Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits. CoRR abs/1507.04523 (2015) - 2014
- [j22]Ronald Ortner
, Daniil Ryabko, Peter Auer
, Rémi Munos:
Regret bounds for restless Markov bandits. Theor. Comput. Sci. 558: 62-76 (2014) - [c48]Peter Auer, Alexander Clark, Thomas Zeugmann, Sandra Zilles:
Editors' Introduction. ALT 2014: 1-7 - [e2]Peter Auer
, Alexander Clark, Thomas Zeugmann, Sandra Zilles:
Algorithmic Learning Theory - 25th International Conference, ALT 2014, Bled, Slovenia, October 8-10, 2014. Proceedings. Lecture Notes in Computer Science 8776, Springer 2014, ISBN 978-3-319-11661-7 [contents] - [i18]Zakria Hussain, Arto Klami, Jussi Kujala, Alex Po Leung, Kitsuchart Pasupa
, Peter Auer, Samuel Kaski, Jorma Laaksonen, John Shawe-Taylor:
PinView: Implicit Feedback in Content-Based Image Retrieval. CoRR abs/1410.0471 (2014) - 2013
- [i17]Peter Auer, Marcus Hutter
, Laurent Orseau:
Reinforcement Learning (Dagstuhl Seminar 13321). Dagstuhl Reports 3(8): 1-26 (2013) - 2012
- [j21]Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor
, Peter Auer:
PAC-Bayesian Inequalities for Martingales. IEEE Trans. Inf. Theory 58(12): 7086-7093 (2012) - [c47]Ronald Ortner
, Daniil Ryabko, Peter Auer
, Rémi Munos:
Regret Bounds for Restless Markov Bandits. ALT 2012: 214-228 - [c46]Yevgeny Seldin, Csaba Szepesvári, Peter Auer, Yasin Abbasi-Yadkori:
Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments. EWRL 2012: 103-116 - [c45]Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, Peter Stone:
PAC Subset Selection in Stochastic Multi-armed Bandits. ICML 2012 - [c44]Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor, Peter Auer:
PAC-Bayesian Inequalities for Martingales. UAI 2012: 12 - [c43]Shiau Hong Lim, Peter Auer:
Autonomous Exploration For Navigating In MDPs. COLT 2012: 40.1-40.24 - [c42]Yevgeny Seldin, Nicolò Cesa-Bianchi, Peter Auer, François Laviolette, John Shawe-Taylor:
PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits. ICML On-line Trading of Exploration and Exploitation 2012: 98-111 - [i16]Shiau Hong Lim, Peter Auer:
Noisy Search with Comparative Feedback. CoRR abs/1202.3741 (2012) - [i15]Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos:
Regret Bounds for Restless Markov Bandits. CoRR abs/1209.2693 (2012) - 2011
- [c41]Peter Auer, Shiau Hong Lim, Chris Watkins:
Models for Autonomously Motivated Exploration in Reinforcement Learning - (Extended Abstract). ALT 2011: 14-17 - [c40]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 - [c39]Peter Auer, Shiau Hong Lim, Chris Watkins:
Models for Autonomously Motivated Exploration in Reinforcement Learning. Discovery Science 2011: 29 - [c38]Peter Auer:
Invited Talk: UCRL and Autonomous Exploration. EWRL 2011: 1 - [c37]Peter Auer:
Exploration and Exploitation in Online Learning. ICAIS 2011: 2 - [c36]Yevgeny Seldin, Peter Auer, François Laviolette, John Shawe-Taylor, Ronald Ortner:
PAC-Bayesian Analysis of Contextual Bandits. NIPS 2011: 1683-1691 - [c35]Shiau Hong Lim, Peter Auer:
Noisy Search with Comparative Feedback. UAI 2011: 445-452 - [p1]Peter Auer, Alex Po Leung:
Relevance Feedback Models for Content-Based Image Retrieval. Multimedia Analysis, Processing and Communications 2011: 59-79 - [i14]Yevgeny Seldin, François Laviolette, John Shawe-Taylor, Jan Peters, Peter Auer:
PAC-Bayesian Analysis of Martingales and Multiarmed Bandits. CoRR abs/1105.2416 (2011) - [i13]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) - [i12]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) - [i11]Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi, John Shawe-Taylor, Peter Auer:
PAC-Bayesian Inequalities for Martingales. CoRR abs/1110.6886 (2011) - 2010
- [j20]Thomas Jaksch, Ronald Ortner, Peter Auer:
Near-optimal Regret Bounds for Reinforcement Learning. J. Mach. Learn. Res. 11: 1563-1600 (2010) - [j19]Peter Auer
, Ronald Ortner
:
UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem. Period. Math. Hung. 61(1-2): 55-65 (2010) - [c34]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 - [c33]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. WAPA 2010: 51-57 - [r2]Peter Auer:
Online Learning. Encyclopedia of Machine Learning 2010: 736-743
2000 – 2009
- 2009
- [c32]Jean-Yves Audibert, Peter Auer, Alessandro Lazaric, Rémi Munos, Daniil Ryabko, Csaba Szepesvári:
Workshop summary: On-line learning with limited feedback. ICML 2009: 8 - [c31]Johann Prankl, Martin Antenreiter, Peter Auer, Markus Vincze:
Consistent Interpretation of Image Sequences to Improve Object Models on the Fly. ICVS 2009: 384-393 - 2008
- [j18]Peter Auer
, Philip M. Long:
Guest editors' introduction: Special issue on learning theory. J. Comput. Syst. Sci. 74(8): 1227 (2008) - [j17]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) - [c30]Alex Po Leung, Peter Auer:
An Efficient Search Algorithm for Content-Based Image Retrieval with User Feedback. ICDM Workshops 2008: 884-890 - [c29]Peter Auer, Thomas Jaksch, Ronald Ortner:
Near-optimal Regret Bounds for Reinforcement Learning. NIPS 2008: 89-96 - [r1]Peter Auer:
Learning with Malicious Noise. Encyclopedia of Algorithms 2008 - 2007
- [j16]Peter Auer
, Ronald Ortner
:
A new PAC bound for intersection-closed concept classes. Mach. Learn. 66(2-3): 151-163 (2007) - [c28]Peter Auer
, Ronald Ortner
, Csaba Szepesvári:
Improved Rates for the Stochastic Continuum-Armed Bandit Problem. COLT 2007: 454-468 - 2006
- [j15]Peter Auer, Nicolò Cesa-Bianchi:
A distributed voting scheme to maximize preferences. RAIRO Theor. Informatics Appl. 40(2): 389-403 (2006) - [j14]Andreas Opelt, Axel Pinz, Michael Fussenegger, Peter Auer:
Generic Object Recognition with Boosting. IEEE Trans. Pattern Anal. Mach. Intell. 28(3): 416-431 (2006) - [c27]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 - [c26]Martin Antenreiter, Christian Savu-Krohn, Peter Auer
:
Visual Classification of Images by Learning Geometric Appearances Through Boosting. ANNPR 2006: 233-243 - [c25]Peter Auer, Ronald Ortner:
Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning. NIPS 2006: 49-56 - 2005
- [c24]Christian Savu-Krohn, Peter Auer:
A Simple Feature Extraction for High Dimensional Image Representations. SLSFS 2005: 163-172 - [e1]Peter Auer, Ron Meir:
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 [contents] - 2004
- [c23]Peter Auer, Ronald Ortner
:
A New PAC Bound for Intersection-Closed Concept Classes. COLT 2004: 408-414 - [c22]Andreas Opelt, Michael Fussenegger, Axel Pinz, Peter Auer:
Weak Hypotheses and Boosting for Generic Object Detection and Recognition. ECCV (2) 2004: 71-84 - [c21]Peter Auer, Ronald Ortner
:
A Boosting Approach to Multiple Instance Learning. ECML 2004: 63-74 - [c20]Michael Fussenegger, Andreas Opelt, Axel Pinz, Peter Auer:
Object Recognition Using Segmentation for Feature Detection. ICPR (3) 2004: 41-44 - 2002
- [j13]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. Inf. Vis. 1(3-4): 166-181 (2002) - [j12]Peter Auer, Nicolò Cesa-Bianchi, Claudio Gentile:
Adaptive and Self-Confident On-Line Learning Algorithms. J. Comput. Syst. Sci. 64(1): 48-75 (2002) - [j11]Peter Auer:
Using Confidence Bounds for Exploitation-Exploration Trade-offs. J. Mach. Learn. Res. 3: 397-422 (2002) - [j10]Peter Auer, Nicolò Cesa-Bianchi, Paul Fischer:
Finite-time Analysis of the Multiarmed Bandit Problem. Mach. Learn. 47(2-3): 235-256 (2002) - [j9]Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire:
The Nonstochastic Multiarmed Bandit Problem. SIAM J. Comput. 32(1): 48-77 (2002) - [c19]Peter Auer, Harald Burgsteiner
, Wolfgang Maass:
Reducing Communication for Distributed Learning in Neural Networks. ICANN 2002: 123-128 - 2000
- [c18]Peter Auer, Claudio Gentile:
Adaptive and Self-Confident On-Line Learning Algorithms. COLT 2000: 107-117 - [c17]Peter Auer:
An Improved On-line Algorithm for Learning Linear Evaluation Functions. COLT 2000: 118-125 - [c16]Peter Auer:
Using Upper Confidence Bounds for Online Learning. FOCS 2000: 270-279 - [i10]Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger:
On the Complexity of Function Learning. Electron. Colloquium Comput. Complex. TR00 (2000) - [i9]Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth:
Learning of Depth Two Neural Networks with Constant Fan-in at the Hidden Nodes. Electron. Colloquium Comput. Complex. TR00 (2000) - [i8]Peter Auer:
On-line Learning of Rectangles in Noisy Environments. Electron. Colloquium Comput. Complex. TR00 (2000) - [i7]Peter Auer:
On Learning from Ambiguous Information. Electron. Colloquium Comput. Complex. TR00 (2000) - [i6]Peter Auer, Philip M. Long:
Simulating Access to Hidden Information while Learning. Electron. Colloquium Comput. Complex. TR00 (2000) - [i5]Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire:
Gambling in a rigged casino: The adversarial multi-armed bandit problem. Electron. Colloquium Comput. Complex. TR00 (2000) - [i4]Peter Auer:
Learning Nested Differences in the Presence of Malicious Noise. Electron. Colloquium Comput. Complex. TR00 (2000) - [i3]Peter Auer, Manfred K. Warmuth:
Tracking the best disjunction. Electron. Colloquium Comput. Complex. TR00 (2000) - [i2]Peter Auer, Nicolò Cesa-Bianchi:
On-line Learning with Malicious Noise and the Closure Algorithm. Electron. Colloquium Comput. Complex. TR00 (2000) - [i1]Peter Auer, Philip M. Long, Aravind Srinivasan:
Approximating Hyper-Rectangles: Learning and Pseudo-random Sets. Electron. Colloquium Comput. Complex. TR00 (2000)
1990 – 1999
- 1999
- [j8]Peter Auer, Philip M. Long:
Structural Results About On-line Learning Models With and Without Queries. Mach. Learn. 36(3): 147-181 (1999) - 1998
- [j7]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) - [j6]Peter Auer, Philip M. Long, Aravind Srinivasan:
Approximating Hyper-Rectangles: Learning and Pseudorandom Sets. J. Comput. Syst. Sci. 57(3): 376-388 (1998) - [j5]Peter Auer, Manfred K. Warmuth:
Tracking the Best Disjunction. Mach. Learn. 32(2): 127-150 (1998) - 1997
- [j4]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) - [j3]Peter Auer:
Learning Nested Differences in the Presence of Malicious Noise. Theor. Comput. Sci. 185(1): 159-175 (1997) - [c15]Peter Auer:
On Learning From Multi-Instance Examples: Empirical Evaluation of a Theoretical Approach. ICML 1997: 21-29 - [c14]Peter Auer, Philip M. Long, Aravind Srinivasan:
Approximating Hyper-Rectangles: Learning and Pseudo-Random Sets. STOC 1997: 314-323 - 1996
- [c13]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 - [c12]Peter Auer, Pasquale Caianiello
, Nicolò Cesa-Bianchi:
Tight Bounds on the Cumulative Profit of Distributed Voters (Abstract). PODC 1996: 312 - 1995
- [j2]Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger:
On the Complexity of Function Learning. Mach. Learn. 18(2-3): 187-230 (1995) - [c11]Peter Auer:
Learning Nested Differences in the Presence of Malicious Noise. ALT 1995: 123-137 - [c10]Peter Auer, Manfred K. Warmuth:
Tracking the Best Disjunction. FOCS 1995: 312-321 - [c9]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 - [c8]Peter Auer, Robert C. Holte, Wolfgang Maass:
Theory and Applications of Agnostic PAC-Learning with Small Decision Trees. ICML 1995: 21-29 - [c7]Peter Auer, Mark Herbster, Manfred K. Warmuth:
Exponentially many local minima for single neurons. NIPS 1995: 316-322 - 1994
- [j1]Kurt Hornik
, Maxwell B. Stinchcombe, Halbert White, Peter Auer:
Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives. Neural Comput. 6(6): 1262-1275 (1994) - [c6]Peter Auer, Nicolò Cesa-Bianchi:
On-line Learning with Malicious Noise and the Closure Algorithm. AII/ALT 1994: 229-247 - [c5]Peter Auer, Philip M. Long:
Simulating access to hidden information while learning. STOC 1994: 263-272 - 1993
- [c4]Peter Auer:
On-Line Learning of Rectangles in Noisy Environments. COLT 1993: 253-261 - [c3]Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger:
On the Complexity of Function Learning. COLT 1993: 392-401 - 1991
- [c2]Peter Auer:
Solving String Equations with Constant Restrictions. IWWERT 1991: 103-132 - [c1]Peter Auer:
Unification in the Combination of Disjoint Theories. IWWERT 1991: 177-186
Coauthor Index
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