On Learning vs. Refutation
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[1] Leonard Pitt,et al. Prediction-Preserving Reducibility , 1990, J. Comput. Syst. Sci..
[2] Benny Applebaum,et al. On Basing Lower-Bounds for Learning on Worst-Case Assumptions , 2008, 2008 49th Annual IEEE Symposium on Foundations of Computer Science.
[3] Salil P. Vadhan,et al. An unconditional study of computational zero knowledge , 2004, 45th Annual IEEE Symposium on Foundations of Computer Science.
[4] Leslie G. Valiant,et al. On the learnability of Boolean formulae , 1987, STOC.
[5] Silvio Micali,et al. How to construct random functions , 1986, JACM.
[6] Amit Daniely,et al. Complexity theoretic limitations on learning halfspaces , 2015, STOC.
[7] Robert E. Schapire,et al. The strength of weak learnability , 1990, Mach. Learn..
[8] Rafail Ostrovsky,et al. One-way functions are essential for non-trivial zero-knowledge , 1993, [1993] The 2nd Israel Symposium on Theory and Computing Systems.
[9] Moni Naor,et al. From Unpredictability to Indistinguishability: A Simple Construction of Pseudo-Random Functions from MACs (Extended Abstract) , 1998, CRYPTO.
[10] Uriel Feige,et al. Resolution lower bounds for the weak pigeon hole principle , 2002, Proceedings 17th IEEE Annual Conference on Computational Complexity.
[11] Leslie G. Valiant,et al. Cryptographic Limitations on Learning Boolean Formulae and Finite Automata , 1993, Machine Learning: From Theory to Applications.
[12] Nathan Linial,et al. From average case complexity to improper learning complexity , 2013, STOC.
[13] Rocco A. Servedio,et al. Learning DNF in time 2Õ(n1/3) , 2004, J. Comput. Syst. Sci..
[14] Andrew Chi-Chih Yao,et al. Theory and Applications of Trapdoor Functions (Extended Abstract) , 1982, FOCS.
[15] Amit Daniely,et al. Complexity Theoretic Limitations on Learning DNF's , 2014, COLT.