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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > SOPHIE LAPLANTE:
All reports by Author Sophie Laplante:

TR26-206 | 22nd September 2026
Chandrima Kayal, Sophie Laplante, Émile Larroque, Krisjanis Prusis, Jevgenijs Vihrovs

Certification complexity of Boolean functions

Certificate complexity $(C(f ))$ is a fundamental measure of complexity of Boolean functions $f$
which counts the number of bits of an input that need to be known in order for the value of the
function to be determined. A certificate can be viewed as a partial assignment, or a ... more >>>


TR23-041 | 1st April 2023
Lila Fontes, Sophie Laplante, Mathieu Lauriere, Alexandre Nolin

The communication complexity of functions with large outputs

We study the two-party communication complexity of functions with large outputs, and show that the communication complexity can greatly vary depending on what output model is considered. We study a variety of output models, ranging from the open model, in which an external observer can compute the outcome, to the ... more >>>


TR22-143 | 7th November 2022
Sourav Chakraborty, Anna Gal, Sophie Laplante, Rajat Mittal, Anupa Sunny

Certificate games

Revisions: 2

We introduce and study Certificate Game complexity, a measure of complexity based on the probability of winning a game where two players are given inputs with different function values and are asked to output some index $i$ such that $x_i\neq y_i$, in a zero-communication setting.

We give upper and lower ... more >>>


TR20-002 | 6th January 2020
Sophie Laplante, Reza Naserasr, Anupa Sunny

Sensitivity lower bounds from linear dependencies

Recently, using spectral techniques, H. Huang proved that every subgraph of the hypercube of dimension n induced on more than half the vertices has maximum degree at least the square root of n. Combined with some earlier work, this completed a proof of the sensitivity conjecture. In this work we ... more >>>


TR15-028 | 27th February 2015
Lila Fontes, Rahul Jain, Iordanis Kerenidis, Sophie Laplante, Mathieu Laurière, Jérémie Roland

Relative Discrepancy does not separate Information and Communication Complexity

Does the information complexity of a function equal its communication complexity? We examine whether any currently known techniques might be used to show a separation between the two notions. Recently, Ganor et al. provided such a separation in the distributional setting for a specific input distribution ?. We show that ... more >>>


TR12-038 | 6th April 2012
Iordanis Kerenidis, Sophie Laplante, Virginie Lerays, Jérémie Roland, David Xiao

Lower bounds on information complexity via zero-communication protocols and applications

We show that almost all known lower bound methods for communication complexity are also lower bounds for the information complexity. In particular, we define a relaxed version of the partition bound of Jain and Klauck and prove that it lower bounds the information complexity of any function. Our relaxed partition ... more >>>


TR12-023 | 19th March 2012
Sophie Laplante, Virginie Lerays, Jérémie Roland

Classical and quantum partition bound and detector inefficiency

In communication complexity, two players each have an input and they wish to compute some function of the joint inputs. This has been the object of much study and a wide variety of lower bound methods have been introduced to address the problem of showing lower bounds on communication. Recently, ... more >>>


TR08-109 | 10th November 2008
Marc Kaplan, Sophie Laplante

Kolmogorov complexity and combinatorial methods in communication complexity

A very important problem in quantum communication complexity is to show that there is, or isn?t, an exponential gap between randomized and quantum complexity for a total function. There are currently no clear candidate functions for such a separation; and there are fewer and fewer randomized lower bound techniques that ... more >>>


TR01-051 | 4th May 2001
Sophie Laplante, Richard Lassaigne, Frederic Magniez, Sylvain Peyronnet, Michel de Rougemont

Probabilistic abstraction for model checking: An approach based on property testing

Revisions: 1

In model checking, program correctness on all inputs is verified
by considering the transition system underlying a given program.
In practice, the system can be intractably large.
In property testing, a property of a single input is verified
by looking at a small subset of that input.
We ... more >>>




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