Publications

Found 23 results
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Szőke G, Nagy C, Hegedüs P, Ferenc R, Gyimóthy T.  2015.  Do Automatic Refactorings Improve Maintainability? An Industrial Case Study Proceedings of the 31st International Conference on Software Maintenance and Evolution – ICSME'15. :429–438.
Szilágyi G, Thanos AM.  2000.  PAGELEARN: Learning Semantic Functions of Attribute Grammars in Parallel.
Szilágyi G., Harmath L., Gyimóthy T..  2001.  The Debug slicing of logic programs. Acta Cybernetica. 15:257–278.
Szilágyi G., Gyimóthy T, Maluszynski J..  1998.  Slicing of Constraint Logic Programs. Linköping Electronic Articles in Computer and Information Science. 3:1-27.
Szilágyi G, Gyimóthy T, Małuszyński J.  2002.  Static and Dynamic Slicing of Constraint Logic Programs. Automated Software Engineering. 9:41–65.
Szilagyi G, Gyimothy T, Maluszynski J.  2000.  Slicing of Constraint Logic Programs. Automated and Algorithmic Debugging.
Szepesvári C., Lörincz A..  1997.  Integrated Architecture for Motion-control and Path-planning. Journal of Robotic Systems. 15:1–15.
Szepesvári C, Lörincz A.  1996.  Approximate geometry representations and sensory fusion. Neurocomputing. 12:267–287.
Szepesvári C.  1997.  The Asymptotic Convergence-Rate of Q-learning. NIPS. :1064–1070.
Szepesvári C., Lörincz A..  1997.  High Precision Neurocontrol of a Chaotic Bioreactor. Nonlinear Analysis. 30:1669–1676.
Szepesvári C, Lörincz A.  1993.  Behavior of an Adaptive Self-organizing Autonomous Agent Working with Cues and Competing Concepts. Adaptive Behaviour. 2:131–160.
Szepesvári C.  1998.  Non-Markovian Policies in Sequential Decision Problems. Acta Cybern.. 13:305-318.
Szepesvári C., Lörincz A..  1997.  Approximate Inverse-Dynamics based Robust Control using Static and Dynamic State Feedback. Applications of Neural Adaptive Control Technology. :151–197.
Szepesvári C.  1997.  Learning and Exploitation Do Not Conflict Under Minimax Optimality. ECML. 1224:242–249.
Szepesvári C, Cimmer S, Lörincz A.  1997.  Neurocontroller using dynamic state feedback for compensatory control. Neural Networks. 10:1691–1708.
Szabó Z, Téglás K, Berta Á, Jelasity M, Bilicki V.  2019.  Stunner: A Smart Phone Trace for Developing Decentralized Edge Systems. Distributed Applications and Interoperable Systems. :108–115.
Stellan O, H SRobert, Turán G, Aaron U.  2017.  Measuring an artificial intelligence system’s performance on a Verbal IQ test for young children. Journal Of Experimental & Theoretical Artificial Intelligence 29. :679-693.
Sloan RH, Turán G.  1999.  On Theory Revision with Queries. Proceedings of the Twelfth Annual Conference on Computational Learning Theory. :41–52.
Sloan RH, Turán G.  1994.  Learning with Queries but Incomplete Information (Extended Abstract). COLT. :237–245.
Sloan RH, Takata K, Turán G.  1998.  On Frequent Sets of Boolean Matrices. Ann. Math. Artif. Intell.. 24:193–209.
Sloan RH, Turán G.  1997.  Learning from Incomplete Boundary Queries Using Split Graphs and Hypergraphs. EuroCOLT. 1208:38–50.
Schrettner L., Gyimóthy T, Alexin Z., Toczki J..  1995.  Parallel execution of object functional queries. Fourth Symposium on Programming Languages and Software Tools. :447-459.
Schrettner L., Gyimóthy T, Alexin Z., Tocki J..  1998.  Parallel execution of object functional queries. Annales Universitatis Scientiarum Budapestinensis de Rolando Eotvos Nominatae Sectio Computarotica. 17:339-355.