Strong Minimax Lower Bounds for Learning. - András Antos; Gábor Lugosi (Mach. Learn., 1998)

Lower Bounds for Bayes Error Estimation. - András Antos; Luc Devroye; László Györfi (IEEE Trans. Pattern Anal. Mach. Intell., 1999)

Performance limits of nonparametric estimators - András Antos (2000)

Data-dependent margin-based generalization bounds for classification. - András Antos; Balázs Kégl; Tamás Linder; Gábor Lugosi (J. Mach. Learn. Res., 2002)

Lower bounds for the rate of convergence in nonparametric pattern recognition. - András Antos (Theor. Comput. Sci., 2002)

Improved convergence rates in empirical vector quantizer design. - András Antos; László Györfi; András György 001 (ISIT, 2004)

Improved minimax bounds on the test and training distortion of empirically designed vector quantizers. - András Antos (IEEE Trans. Inf. Theory, 2005)

Individual convergence rates in empirical vector quantizer design. - András Antos; László Györfi; András György 001 (IEEE Trans. Inf. Theory, 2005)

Fitted Q-iteration in continuous action-space MDPs. - András Antos; Rémi Munos; Csaba Szepesvári (NIPS, 2007)

Active Learning in Multi-armed Bandits. - András Antos; Varun Grover; Csaba Szepesvári (ALT, 2008)

Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path. - András Antos; Csaba Szepesvári; Rémi Munos (Mach. Learn., 2008)

Active learning in heteroscedastic noise. - András Antos; Varun Grover; Csaba Szepesvári (Theor. Comput. Sci., 2010)

Non-trivial two-armed partial-monitoring games are bandits - András Antos; Gábor Bartók; Csaba Szepesvári (CoRR, 2011)

On Codecell Convexity of Optimal Multiresolution Scalar Quantizers for Continuous Sources. - András Antos (IEEE Trans. Inf. Theory, 2012)

Toward a classification of finite partial-monitoring games. - András Antos; Gábor Bartók; Dávid Pál; Csaba Szepesvári (Theor. Comput. Sci., 2013)

Online Markov Decision Processes Under Bandit Feedback. - Gergely Neu; András György 001; Csaba Szepesvári; András Antos (IEEE Trans. Autom. Control., 2014)

Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits. - Alexandra Carpentier; Alessandro Lazaric; Mohammad Ghavamzadeh; Rémi Munos; Peter Auer; András Antos (CoRR, 2015)

Adaptive strategy for stratified Monte Carlo sampling. - Alexandra Carpentier; Rémi Munos; András Antos (J. Mach. Learn. Res., 2015)

Boosting Multitask Decomposition: Directness, Sequentiality, Subsampling, Cross-Gradients. - András Millinghoffer; Mátyás Antal; Márk Marosi; András Formanek; András Antos; Péter Antal (AIME (1), 2024)