Peter Auer

Orcid: 0000-0001-8385-9635

According to our database1, Peter Auer authored at least 91 papers between 1991 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

Legend:

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On csauthors.net:

Bibliography

2023
The bin covering with delivery problem, extended investigations for the online case.
Central Eur. J. Oper. Res., March, 2023

Detecting Anomalous Multivariate Time-Series via Hybrid Machine Learning.
IEEE Trans. Instrum. Meas., 2023

Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022
Hybrid Machine Learning for Anomaly Detection in Industrial Time-Series Measurement Data.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2022

2021
A new heuristic and an exact approach for a production planning problem.
Central Eur. J. Oper. Res., 2021

Learning to Drive with Deep Reinforcement Learning.
Proceedings of the 13th International Conference on Knowledge and Smart Technology, 2021

Particle Size Estimation in Mixed Commercial Waste Images Using Deep Learning.
Proceedings of the IAIT 2021: The 12th International Conference on Advances in Information Technology, Bangkok, Thailand, 29 June 2021, 2021

2019
Autonomous exploration for navigating in non-stationary CMPs.
CoRR, 2019

Variational Regret Bounds for Reinforcement Learning.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes.
Proceedings of the Conference on Learning Theory, 2019

Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information.
Proceedings of the Conference on Learning Theory, 2019

2018
Online Learning With Randomized Feedback Graphs for Optimal PUE Attacks in Cognitive Radio Networks.
IEEE/ACM Trans. Netw., 2018

A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions.
CoRR, 2018

2017
Online Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Optimal Online Learning with Randomized Feedback Graphs with Application in PUE Attacks in CRN.
CoRR, 2017

2016
Learning with Malicious Noise.
Encyclopedia of Algorithms, 2016

Guest editors' foreword.
Theor. Comput. Sci., 2016

An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits.
Proceedings of the 29th Conference on Learning Theory, 2016

Pareto Front Identification from Stochastic Bandit Feedback.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits.
CoRR, 2015

2014
Regret bounds for restless Markov bandits.
Theor. Comput. Sci., 2014

Editors' Introduction.
Proceedings of the Algorithmic Learning Theory - 25th International Conference, 2014

2013
Reinforcement Learning (Dagstuhl Seminar 13321).
Dagstuhl Reports, 2013

2012
PAC-Bayesian Inequalities for Martingales.
IEEE Trans. Inf. Theory, 2012

PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits.
Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, 2012

Autonomous Exploration For Navigating In MDPs.
Proceedings of the COLT 2012, 2012

PAC Subset Selection in Stochastic Multi-armed Bandits.
Proceedings of the 29th International Conference on Machine Learning, 2012

Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments.
Proceedings of the Tenth European Workshop on Reinforcement Learning, 2012

2011
Relevance Feedback Models for Content-Based Image Retrieval.
Proceedings of the Multimedia Analysis, Processing and Communications, 2011

PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off
CoRR, 2011

PAC-Bayesian Analysis of Martingales and Multiarmed Bandits
CoRR, 2011

Noisy Search with Comparative Feedback.
Proceedings of the UAI 2011, 2011

PAC-Bayesian Analysis of Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Exploration and Exploitation in Online Learning.
Proceedings of the Adaptive and Intelligent Systems - Second International Conference, 2011

Invited Talk: UCRL and Autonomous Exploration.
Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

Models for Autonomously Motivated Exploration in Reinforcement Learning.
Proceedings of the Discovery Science - 14th International Conference, 2011

Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits.
Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

Models for Autonomously Motivated Exploration in Reinforcement Learning - (Extended Abstract).
Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

2010
Online Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem.
Period. Math. Hung., 2010

Near-optimal Regret Bounds for Reinforcement Learning.
J. Mach. Learn. Res., 2010

Pinview: Implicit Feedback in Content-Based Image Retrieval.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009
Consistent Interpretation of Image Sequences to Improve Object Models on the Fly.
Proceedings of the Computer Vision Systems, 2009

Workshop summary: On-line learning with limited feedback.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Learning with Malicious Noise.
Proceedings of the Encyclopedia of Algorithms - 2008 Edition, 2008

A learning rule for very simple universal approximators consisting of a single layer of perceptrons.
Neural Networks, 2008

Guest editors' introduction: Special issue on learning theory.
J. Comput. Syst. Sci., 2008

An Efficient Search Algorithm for Content-Based Image Retrieval with User Feedback.
Proceedings of the Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007
A new PAC bound for intersection-closed concept classes.
Mach. Learn., 2007

Improved Rates for the Stochastic Continuum-Armed Bandit Problem.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
Generic Object Recognition with Boosting.
IEEE Trans. Pattern Anal. Mach. Intell., 2006

A distributed voting scheme to maximize preferences.
RAIRO Theor. Informatics Appl., 2006

Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Visual Classification of Images by Learning Geometric Appearances Through Boosting.
Proceedings of the Artificial Neural Networks in Pattern Recognition, Second IAPR Workshop, 2006

Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring.
Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

2005
A Simple Feature Extraction for High Dimensional Image Representations.
Proceedings of the Subspace, 2005

2004
Object Recognition Using Segmentation for Feature Detection.
Proceedings of the 17th International Conference on Pattern Recognition, 2004

A Boosting Approach to Multiple Instance Learning.
Proceedings of the Machine Learning: ECML 2004, 2004

Weak Hypotheses and Boosting for Generic Object Detection and Recognition.
Proceedings of the Computer Vision, 2004

2002
The Nonstochastic Multiarmed Bandit Problem.
SIAM J. Comput., 2002

Finite-time Analysis of the Multiarmed Bandit Problem.
Mach. Learn., 2002

Using Confidence Bounds for Exploitation-Exploration Trade-offs.
J. Mach. Learn. Res., 2002

Adaptive and Self-Confident On-Line Learning Algorithms.
J. Comput. Syst. Sci., 2002

The InfoSky visual explorer: exploiting hierarchical structure and document similarities.
Inf. Vis., 2002

Reducing Communication for Distributed Learning in Neural Networks.
Proceedings of the Artificial Neural Networks, 2002

2000
Approximating Hyper-Rectangles: Learning and Pseudo-random Sets
Electron. Colloquium Comput. Complex., 2000

Gambling in a rigged casino: The adversarial multi-armed bandit problem
Electron. Colloquium Comput. Complex., 2000

Simulating Access to Hidden Information while Learning
Electron. Colloquium Comput. Complex., 2000

On Learning from Ambiguous Information
Electron. Colloquium Comput. Complex., 2000

On-line Learning of Rectangles in Noisy Environments
Electron. Colloquium Comput. Complex., 2000

Learning of Depth Two Neural Networks with Constant Fan-in at the Hidden Nodes
Electron. Colloquium Comput. Complex., 2000

Using Upper Confidence Bounds for Online Learning.
Proceedings of the 41st Annual Symposium on Foundations of Computer Science, 2000

Adaptive and Self-Confident On-Line Learning Algorithms.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

An Improved On-line Algorithm for Learning Linear Evaluation Functions.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999
Structural Results About On-line Learning Models With and Without Queries.
Mach. Learn., 1999

1998
Tracking the Best Disjunction.
Mach. Learn., 1998

Approximating Hyper-Rectangles: Learning and Pseudorandom Sets.
J. Comput. Syst. Sci., 1998

On-Line Learning with Malicious Noise and the Closure Algorithm.
Ann. Math. Artif. Intell., 1998

1997
Learning Nested Differences in the Presence of Malicious Noise.
Theor. Comput. Sci., 1997

The Perceptron Algorithm Versus Winnow: Linear Versus Logarithmic Mistake Bounds when Few Input Variables are Relevant (Technical Note).
Artif. Intell., 1997

On Learning From Multi-Instance Examples: Empirical Evaluation of a Theoretical Approach.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

1996
Tight Bounds on the Cumulative Profit of Distributed Voters (Abstract).
Proceedings of the Fifteenth Annual ACM Symposium on Principles of Distributed Computing, 1996

Learning of Depth Two Neural Networks with Constant Fan-In at the Hidden Nodes (Extended Abstract).
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995
On the Complexity of Function Learning.
Mach. Learn., 1995

Exponentially many local minima for single neurons.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Theory and Applications of Agnostic PAC-Learning with Small Decision Trees.
Proceedings of the Machine Learning, 1995

Gambling in a Rigged Casino: The Adversarial Multi-Arm Bandit Problem.
Proceedings of the 36th Annual Symposium on Foundations of Computer Science, 1995

1994
Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives.
Neural Comput., 1994

1991
Unification in the Combination of Disjoint Theories.
Proceedings of the Word Equations and Related Topics, Second International Workshop, 1991

Solving String Equations with Constant Restrictions.
Proceedings of the Word Equations and Related Topics, Second International Workshop, 1991


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