Improved Algorithms for Theory Revision with Queries. - Judy Goldsmith; Robert H. Sloan; Balázs Szörényi; György Turán (COLT, 2000)

New Revision Algorithms. - Judy Goldsmith; Robert H. Sloan; Balázs Szörényi; György Turán (ALT, 2004)

Theory revision with queries: Horn, read-once, and parity formulas. - Judy Goldsmith; Robert H. Sloan; Balázs Szörényi; György Turán (Artif. Intell., 2004)

On k-term DNF with largest number of prime implicants - Robert H. Sloan; Balázs Szörényi; György Turán (Electron. Colloquium Comput. Complex., 2005)

Revising threshold functions. - Robert H. Sloan; Balázs Szörényi; György Turán (Theor. Comput. Sci., 2007)

Horn Complements: Towards Horn-to-Horn Belief Revision. - Marina Langlois; Robert H. Sloan; Balázs Szörényi; György Turán (AAAI, 2008)

Projective DNF formulae and their revision. - Robert H. Sloan; Balázs Szörényi; György Turán (Discret. Appl. Math., 2008)

Disjoint DNF Tautologies with Conflict Bound Two. - Balázs Szörényi (J. Satisf. Boolean Model. Comput., 2008)

Characterizing Statistical Query Learning: Simplified Notions and Proofs. - Balázs Szörényi (ALT, 2009)

Learning Boolean Functions with Queries. - Robert H. Sloan; Balázs Szörényi; György Turán; Yves Crama; Peter L. Hammer (Boolean Models and Methods, 2010)

One-inclusion hypergraph density revisited. - Hans Ulrich Simon; Balázs Szörényi (Inf. Process. Lett., 2010)

Horn Belief Contraction: Remainders, Envelopes and Complexity. - Kira V. Adaricheva; Robert H. Sloan; Balázs Szörényi; György Turán (KR, 2012)

Top-k Selection based on Adaptive Sampling of Noisy Preferences. - Róbert Busa-Fekete; Balázs Szörényi; Weiwei Cheng; Paul Weng; Eyke Hüllermeier (ICML (3), 2013)

Gossip-based distributed stochastic bandit algorithms. - Balázs Szörényi; Róbert Busa-Fekete; István Hegedüs; Róbert Ormándi; Márk Jelasity; Balázs Kégl (ICML (3), 2013)

Unlabeled Data Does Provably Help. - Malte Darnstädt; Hans Ulrich Simon; Balázs Szörényi (STACS, 2013)

PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences. - Róbert Busa-Fekete; Balázs Szörényi; Eyke Hüllermeier (AAAI, 2014)

Biclique Coverings, Rectifier Networks and the Cost of ε-Removal. - Szabolcs Iván; Ádám Dániel Lelkes; Judit Nagy-György; Balázs Szörényi; György Turán (DCFS, 2014)

Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows. - Róbert Busa-Fekete; Eyke Hüllermeier; Balázs Szörényi (ICML, 2014)

Optimistic Planning in Markov Decision Processes Using a Generative Model. - Balázs Szörényi; Gunnar Kedenburg; Rémi Munos (NIPS, 2014)

Biclique coverings, rectifier networks and the cost of $ varepsilon$-removal. - Szabolcs Iván; Ádám Dániel Lelkes; Judit Nagy-György; Balázs Szörényi; György Turán (CoRR, 2014)

Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm. - Róbert Busa-Fekete; Balázs Szörényi; Paul Weng; Weiwei Cheng; Eyke Hüllermeier (Mach. Learn., 2014)

Supervised learning and Co-training. - Malte Darnstädt; Hans Ulrich Simon; Balázs Szörényi (Theor. Comput. Sci., 2014)

Qualitative Multi-Armed Bandits: A Quantile-Based Approach. - Balázs Szörényi; Róbert Busa-Fekete; Paul Weng; Eyke Hüllermeier (ICML, 2015)

Online F-Measure Optimization. - Róbert Busa-Fekete; Balázs Szörényi; Krzysztof Dembczynski; Eyke Hüllermeier (NIPS, 2015)

Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach. - Balázs Szörényi; Róbert Busa-Fekete; Adil Paul; Eyke Hüllermeier (NIPS, 2015)

Distributed Clustering of Linear Bandits in Peer to Peer Networks. - Nathan Korda; Balázs Szörényi; Shuai Li (ICML, 2016)

Multi-objective Bandits: Optimizing the Generalized Gini Index. - Róbert Busa-Fekete; Balázs Szörényi; Paul Weng; Shie Mannor (ICML, 2017)

Non-parametric Online AUC Maximization. - Balázs Szörényi; Snir Cohen; Shie Mannor (ECML/PKDD (2), 2017)

Concentration Bounds for Two Timescale Stochastic Approximation with Applications to Reinforcement Learning. - Gal Dalal; Balázs Szörényi; Gugan Thoppe; Shie Mannor (CoRR, 2017)

Finite Sample Analysis for TD(0) with Linear Function Approximation. - Gal Dalal; Balázs Szörényi; Gugan Thoppe; Shie Mannor (CoRR, 2017)

Finite Sample Analyses for TD(0) With Function Approximation. - Gal Dalal; Balázs Szörényi; Gugan Thoppe; Shie Mannor (AAAI, 2018)

Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning. - Gal Dalal; Gugan Thoppe; Balázs Szörényi; Shie Mannor (COLT, 2018)

PAC Bandits with Risk Constraints. - Yahel David; Balázs Szörényi; Mohammad Ghavamzadeh; Shie Mannor; Nahum Shimkin (ISAIM, 2018)

Optimal Learning of Mallows Block Model. - Róbert Busa-Fekete; Dimitris Fotakis 001; Balázs Szörényi; Manolis Zampetakis (COLT, 2019)

Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. - Alina Beygelzimer; Dávid Pál; Balázs Szörényi; Devanathan Thiruvenkatachari; Chen-Yu Wei; Chicheng Zhang (ICML, 2019)

The information-theoretic value of unlabeled data in semi-supervised learning. - Alexander Golovnev; Dávid Pál; Balázs Szörényi (ICML, 2019)

A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound. - Gal Dalal; Balázs Szörényi; Gugan Thoppe (AAAI, 2020)

Learning to Crawl. - Utkarsh Upadhyay; Róbert Busa-Fekete; Wojciech Kotlowski; Dávid Pál; Balázs Szörényi (AAAI, 2020)

Identity testing for Mallows model. - Róbert Busa-Fekete; Dimitris Fotakis 001; Balázs Szörényi; Emmanouil Zampetakis (NeurIPS, 2021)

Regret Bounds for Multilabel Classification in Sparse Label Regimes. - Róbert Busa-Fekete; Heejin Choi; Krzysztof Dembczynski; Claudio Gentile; Henry Reeve; Balázs Szörényi (NeurIPS, 2022)