Years and Authors of Summarized Original Work
1986; Babai, Frankl, Simon
2004; Bar-Yossef, Jayram, Kumar, Sivakumar
2010; Barak, Braverman, Chen, Rao
2012; Braverman
2011; Braverman, Rao
2014; Brody, Chakrabarti, Kondapally, Woodruff, Yaroslavtsev
2012; Chakrabarti, Regev
2001; Chakrabarti, Shi, Wirth, Yao
1995; Feder, Kushilevitz, Naor, Nisan
2014; Ganor, Kol, Raz
2010; Jain, Klauck
1997; Kushilevitz, Nisan
2009; Lee, Shraibman
2014; Lovett
1998; Miltersen, Nisan, Safra, Wigderson
1991; Newman
1992; Razborov
1977; Yao
1979; Yao
Problem Definition
Two players – Alice and Bob – are playing a game in which their shared goal is to compute a function \(f : \mathcal{X}\times \mathcal{Y}\rightarrow \mathcal{Z}\) efficiently. The game starts with Alice holding a value \(x \in \mathcal{X}\) and Bob holding \(y \in \mathcal{Y}\). They then communicate by sending each other messages according to a predetermined protocol, at the end of which they must both arrive at some output \(z \in...
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Alon N, Matias Y, Szegedy M (1999) The space complexity of approximating the frequency moments. J Comput Syst Sci 58(1):137–147. Preliminary version in Proceedings of the 28th annual ACM Symposium on the Theory of Computing, 1996, pp 20–29
Babai L, Frankl P, Simon J (1986) Complexity classes in communication complexity theory. In: Proceedings of the 27th annual IEEE Symposium on Foundations of Computer Science, Toronto, pp 337–347
Barak B, Braverman M, Chen X, Rao A (2010) How to compress interactive communication. In: Proceedings of the 41st annual ACM Symposium on the Theory of Computing, Cambridge, pp 67–76
Bar-Yossef Z, Jayram TS, Kumar R, Sivakumar D (2004) An information statistics approach to data stream and communication complexity. J Comput Syst Sci 68(4):702–732
Braverman M (2012) Interactive information complexity. In: Proceedings of the 44th annual ACM Symposium on the Theory of Computing, New York, pp 505–524
Braverman M, Rao A (2011) Information equals amortized communication. In: Proceedings of the 52nd annual IEEE Symposium on Foundations of Computer Science, Palm Springs, pp 748–757
Brody J, Chakrabarti A, Kondapally R, Woodruff DP, Yaroslavtsev G (2014) Certifying equality with limited interaction. In: Proceedings of the 18th international workshop on randomization and approximation techniques in computer science,Barcelona, pp 545–581
Chakrabarti A, Regev O (2012) An optimal lower bound on the communication complexity of GAP-HAMMING-DISTANCE. SIAM J Comput 41(5):1299–1317. Preliminary version in Proceedings of the 43rd annual ACM symposium on the theory of computing, 2011, pp 51–60
Chakrabarti A, Shi Y, Wirth A, Yao AC (2001) Informational complexity and the direct sum problem for simultaneous message complexity. In: Proceedings of the 42nd annual IEEE Symposium on Foundations of Computer Science, Las Vegas, pp 270–278
Feder T, Kushilevitz E, Naor M, Nisan N (1995) Amortized communication complexity. SIAM J Comput 24(4):736–750. Preliminary version in Proceedings of the 32nd annual IEEE symposium on foundations of computer science, 1991, pp 239–248
Ganor A, Kol G, Raz R (2014) Exponential separation of information and communication for boolean functions. Technical report TR14-113, ECCC
Jain R, Klauck H (2010) The partition bound for classical communication complexity and query complexity. In: Proceedings of the 25th annual IEEE Conference on Computational Complexity, Cambridge, pp 247–258
Karchmer M, Wigderson A (1990) Monotone circuits for connectivity require super-logarithmic depth. SIAM J Discrete Math 3(2):255–265. Preliminary version in Proceedings of the 20th annual ACM symposium on the theory of computing, 1988, pp 539–550
Kushilevitz E, Nisan N (1997) Communication complexity. Cambridge University Press, Cambridge
Lee T, Shraibman A (2009) Lower bounds in communication complexity. Found Trends Theor Comput Sci 3(4):263–399
Lovett S (2014) Communication is bounded by root of rank. In: Proceedings of the 46th annual ACM Symposium on the Theory of Computing, New York, pp 842–846
Miltersen PB, Nisan N, Safra S, Wigderson A (1998) On data structures and asymmetric communication complexity. J Comput Syst Sci 57(1):37–49. Preliminary version in Proceedings of the 27th annual ACM Symposium on the Theory of Computing, 1995, pp 103–111
Newman I (1991) Private vs. common random bits in communication complexity. Inf Process Lett 39(2):67–71
Pǎtraşcu M (2011) Unifying the landscape of cell-probe lower bounds. SIAM J Comput 40(3):827–847
Razborov A (1992) On the distributional complexity of disjointness. Theor Comput Sci 106(2):385–390. Preliminary version in Proceedings of the 17th international colloquium on automata, languages and programming, 1990, pp 249–253
Sherstov AA (2014) Communication lower bounds using directional derivatives. J. ACM 61(6):34:1–34:71. Preliminary version in Proceedings of the 45th annual ACM Symposium on the Theory of Computing, 2013, pp 921–930
Yao AC (1977) Probabilistic computations: towards a unified measure of complexity. In: Proceedings of the 18th annual IEEE Symposium on Foundations of Computer Science, Providence, pp 222–227
Yao AC (1979) Some complexity questions related to distributive computing. In: Proceedings of the 11th annual ACM Symposium on the Theory of Computing, Atlanta, pp 209–213
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Chakrabarti, A. (2015). Communication Complexity. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27848-8_799-1
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