1. Agrawal, R.: Samplers and extractors for unbounded functions. In: Achlioptas, D., Végh, L.A. (eds.) Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019), volume 145 of Leibniz International Proceedings in Informatics (LIPIcs), pp. 59:1–59:21, Dagstuhl, Germany (2019). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik
2. Lecture Notes in Computer Science;B Auerbach,2017
3. Lecture Notes in Computer Science;Y Aumann,1999
4. Lecture Notes in Computer Science;B Barak,2011
5. Beame, P., Gharan, S.O., Yang, X.: Time-space tradeoffs for learning finite functions from random evaluations, with applications to polynomials. In: Bubeck, S., Perchet, V., Rigollet, P. (eds.) Conference On Learning Theory, COLT 2018, volume 75 of Proceedings of Machine Learning Research, Stockholm, Sweden, 6–9 July 2018, pp. 843–856. PMLR (2018)