Communication complexity
On randomized one-round communication complexity
Computational Complexity
New applications of the incompressibility method: part II
Theoretical Computer Science - Selected papers in honor of Manuel Blum
Two applications of information complexity
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Some complexity questions related to distributive computing(Preliminary Report)
STOC '79 Proceedings of the eleventh annual ACM symposium on Theory of computing
Information Theory Methods in Communication Complexity
CCC '02 Proceedings of the 17th IEEE Annual Conference on Computational Complexity
Informational Complexity and the Direct Sum Problem for Simultaneous Message Complexity
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
An information statistics approach to data stream and communication complexity
Journal of Computer and System Sciences - Special issue on FOCS 2002
Individual communication complexity
Journal of Computer and System Sciences
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
A Direct Product Theorem for Discrepancy
CCC '08 Proceedings of the 2008 IEEE 23rd Annual Conference on Computational Complexity
Randomised Individual Communication Complexity
CCC '08 Proceedings of the 2008 IEEE 23rd Annual Conference on Computational Complexity
On determinism versus non-determinism and related problems
SFCS '83 Proceedings of the 24th Annual Symposium on Foundations of Computer Science
Exponential Separation of Quantum and Classical One-Way Communication Complexity
SIAM Journal on Computing
Lower Bounds for Randomized and Quantum Query Complexity Using Kolmogorov Arguments
SIAM Journal on Computing
An Introduction to Kolmogorov Complexity and Its Applications
An Introduction to Kolmogorov Complexity and Its Applications
Lower bounds in communication complexity based on factorization norms
Random Structures & Algorithms
SIAM Journal on Computing
Evaluation of analogical proportions through Kolmogorov complexity
Knowledge-Based Systems
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We introduce a method based on Kolmogorov complexity to prove lower bounds on communication complexity. The intuition behind our technique is close to information theoretic methods. We use Kolmogorov complexity for three different things: first, to give a general lower bound in terms of Kolmogorov mutual information; second, to prove an alternative to Yao's minmax principle based on Kolmogorov complexity; and finally, to identify hard inputs. We show that our method implies the rectangle and corruption bounds, known to be closely related to the subdistribution bound. We apply our method to the hidden matching problem, a relation introduced to prove an exponential gap between quantum and classical communication. We then show that our method generalizes the VC dimension and shatter coefficient lower bounds. Finally, we compare one-way communication and simultaneous communication in the case of distributional communication complexity and improve the previous known result.