Balázs Szörényi

According to our database1, Balázs Szörényi authored at least 40 papers between 2000 and 2022.

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Bibliography

2022
Regret Bounds for Multilabel Classification in Sparse Label Regimes.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Identity testing for Mallows model.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Learning to Crawl.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
The information-theoretic value of unlabeled data in semi-supervised learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case.
Proceedings of the 36th International Conference on Machine Learning, 2019

Optimal Learning of Mallows Block Model.
Proceedings of the Conference on Learning Theory, 2019

2018
PAC Bandits with Risk Constraints.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2018

Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning.
Proceedings of the Conference On Learning Theory, 2018

Finite Sample Analyses for TD(0) With Function Approximation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Finite Sample Analysis for TD(0) with Linear Function Approximation.
CoRR, 2017

Concentration Bounds for Two Timescale Stochastic Approximation with Applications to Reinforcement Learning.
CoRR, 2017

Non-parametric Online AUC Maximization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Multi-objective Bandits: Optimizing the Generalized Gini Index.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Distributed Clustering of Linear Bandits in Peer to Peer Networks.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Online F-Measure Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Qualitative Multi-Armed Bandits: A Quantile-Based Approach.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Supervised learning and Co-training.
Theor. Comput. Sci., 2014

Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm.
Mach. Learn., 2014

Biclique coverings, rectifier networks and the cost of $\varepsilon$-removal.
CoRR, 2014

Optimistic Planning in Markov Decision Processes Using a Generative Model.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows.
Proceedings of the 31th International Conference on Machine Learning, 2014

Biclique Coverings, Rectifier Networks and the Cost of ε-Removal.
Proceedings of the Descriptional Complexity of Formal Systems, 2014

PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Unlabeled Data Does Provably Help.
Proceedings of the 30th International Symposium on Theoretical Aspects of Computer Science, 2013

Gossip-based distributed stochastic bandit algorithms.
Proceedings of the 30th International Conference on Machine Learning, 2013

Top-k Selection based on Adaptive Sampling of Noisy Preferences.
Proceedings of the 30th International Conference on Machine Learning, 2013

2011
Horn Belief Contraction: Remainders, Envelopes and Complexity.
Proceedings of the Logical Formalizations of Commonsense Reasoning, 2011

2010
One-inclusion hypergraph density revisited.
Inf. Process. Lett., 2010

Learning Boolean Functions with Queries.
Proceedings of the Boolean Models and Methods in Mathematics, 2010

2009
Characterizing Statistical Query Learning: Simplified Notions and Proofs.
Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009

2008
On k-Term DNF with the Largest Number of Prime Implicants.
SIAM J. Discret. Math., 2008

Disjoint DNF Tautologies with Conflict Bound Two.
J. Satisf. Boolean Model. Comput., 2008

Projective DNF formulae and their revision.
Discret. Appl. Math., 2008

Horn Complements: Towards Horn-to-Horn Belief Revision.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Revising threshold functions.
Theor. Comput. Sci., 2007

2004
Theory revision with queries: Horn, read-once, and parity formulas.
Artif. Intell., 2004

New Revision Algorithms.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2000
Improved Algorithms for Theory Revision with Queries.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000


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