András Antos - researchr alias

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Viewing Publication 1 - 20 from 20

2015

Adaptive strategy for stratified Monte Carlo samplingAlexandra Carpentier, Rémi Munos, András Antos. jmlr, 16:2231-2271, 2015. [doi]

2014

Online Markov Decision Processes Under Bandit FeedbackGergely Neu, András György, Csaba Szepesvári, András Antos. tac, 59(3):676-691, 2014. [doi]

2013

Toward a classification of finite partial-monitoring gamesAndrás Antos, Gábor Bartók, Dávid Pál, Csaba Szepesvári. TCS, 473:77-99, 2013. [doi]

2012

On Codecell Convexity of Optimal Multiresolution Scalar Quantizers for Continuous SourcesAndrás Antos. TIT, 58(2):1147-1157, 2012. [doi]

2010

Active learning in heteroscedastic noiseAndrás Antos, Varun Grover, Csaba Szepesvári. TCS, 411(29-30):2712-2728, 2010. [doi]

Online Markov Decision Processes under Bandit FeedbackGergely Neu, András György, Csaba Szepesvári, András Antos. nips 2010: 1804-1812 [doi]

2008

Active Learning in Multi-armed BanditsAndrás Antos, Varun Grover, Csaba Szepesvári. alt 2008: 287-302 [doi]

Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample pathAndrás Antos, Csaba Szepesvári, Rémi Munos. ml, 71(1):89-129, 2008. [doi]

2007

Fitted Q-iteration in continuous action-space MDPsAndrás Antos, Rémi Munos, Csaba Szepesvári. nips 2008: 9-16 [doi]

2006

Learning Near-Optimal Policies with Bellman-Residual Minimization Based Fitted Policy Iteration and a Single Sample PathAndrás Antos, Csaba Szepesvári, Rémi Munos. colt 2006: 574-588 [doi]

2005

Improved minimax bounds on the test and training distortion of empirically designed vector quantizersAndrás Antos. TIT, 51(11):4022-4032, 2005. [doi]

Improved Minimax Bounds on the Test and Training Distortion of Empirically Designed Vector QuantizersAndrás Antos. colt 2005: 531-544 [doi]

Individual convergence rates in empirical vector quantizer designAndrás Antos, László Györfi, A. Gyorgy. TIT, 51(11):4013-4022, 2005. [doi]

2004

Improved convergence rates in empirical vector quantizer designAndrás Antos, László Györfi, András György. isit 2004: 301 [doi]

2002

Lower bounds for the rate of convergence in nonparametric pattern recognitionAndrás Antos. TCS, 284(1):3-24, 2002. [doi]

Data-dependent margin-based generalization bounds for classificationAndrás Antos, Balázs Kégl, Tamás Linder, Gábor Lugosi. jmlr, 3:73-98, 2002. [doi]

1999

Lower Bounds on the Rate of Convergence of Nonparametric Pattern RecognitionAndrás Antos. eurocolt 1999: 241-252 [doi]

Lower Bounds for Bayes Error EstimationAndrás Antos, Luc Devroye, László Györfi. pami, 21(7):643-645, 1999. [doi]

1998

Strong Minimax Lower Bounds for LearningAndrás Antos, Gábor Lugosi. ml, 30(1):31-56, 1998.

1996

Strong Minimax Lower Bounds for LearningAndrás Antos, Gábor Lugosi. colt 1996: 303-309 [doi]

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