Journals

• Robert H. Sloan, Balázs Szörényi, and György Turán
  On k-term DNF with largest number of prime implicants
  SIAM Journal on Discrete Mathematics, 21(4): 987 -- 998, Jan. 2008.
• Robert H. Sloan, Balázs Szörényi, and György Turán
  Projective DNF formulae and their revision
  Discrete Applied Mathematics, 156: 530 -- 544, 2008.

• Robert H. Sloan, Balázs Szörényi, and György Turán
  Revising threshold functions
  Theoretical Computer Science, 382(3): 198 -- 208, 2007. (ALT 2004 Special Issue.)
• Balázs Szörényi
  Disjoint DNF tautologies with conflict bound two
  Journal on Satisfiability, Boolean Modeling and Computation, 4: 1 -- 14, 2007.
• Judy Goldsmith, Robert H. Sloan, Balázs Szörényi, and György Turán
  Theory revision with queries: Horn, read-once, and parity formulas
  Artificial Intelligence, 156:139 -- 176, 2004.

Proceedings

• Marina Langlois, Robert H. Sloan, Balázs Szörényi, and György Turán
  Horn Complements: Towards Horn-to-Horn belief revision
  Twenty-Third AAAI Conference on Artificial Intelligence (AAAI-08), AAAI Press, 466 -- 471, 2008.
  
• Judy Goldsmith, Robert H. Sloan, Balázs Szörényi, and György Turán
  Theory revision with queries: results and problems.
  Workshop on Learning with Logic and Logics for Learning (LLLL), Japanese Society for AI, 39 -- 44, 2005.
• Judy Goldsmith, Robert H. Sloan, Balázs Szörényi, and György Turán
  New revision algorithms.
  15th Algorithmic Learning Theory (ALT 2004), Springer LNAI 3244, 395 -- 409, 2004.
• Robert H. Sloan, Balázs Szörényi, and György Turán
  Projective DNF formulae and their revision
  Learning Theory and Kernel Machines (16th COLT/Kernel 2003), Springer LNAI 2777, 625 -- 639, 2003.
• Robert H. Sloan and Balázs Szörényi
  Revising projective DNF in the presence of noise.
  In Proc. Kalmár Workshop on Logic and Computer Science, October 2003, pages 143 -- 152.
  
• Judy Goldsmith, Robert H. Sloan, Balázs Szörényi, and György Turán
  Improved algorithms for theory revision with queries.
  13th Annual Conference on Computational Learning Theory (13th COLT), 236 -- 247, 2000.