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Maryse Pelletier

dblp:35/6733 · DBLP profile ↗
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4ranked-venue papers
3as first author
0since 2021 · last 2011
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 4 · 3 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
3 papers
Algorithms and data structures · 64% Information theory · 32% Automata and formal languages · 4%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures › randomized algorithms › sampling › random variate generation
discrete distribution sampling
0.112011
On Buffon Machines and Numbers · SODA 2011
Information theory
random number generation
0.112011
On Buffon Machines and Numbers · SODA 2011
Algorithms and data structures › randomized algorithms
sampling
0.112011
On Buffon Machines and Numbers · SODA 2011
Automata and formal languages › algebraic language theory
rational subsets
0.011990
Boolean Closure and Unambiguity of Rational Sets · ICALP 1990
Algorithms and data structures › symbolic computation › computational algebra › algebraic algorithms
multiplication
0.011990
Easy Multiplications II. Extensions of Rational Semigroups · Inf. Comput. 1990
Automata and formal languages › context-free languages
unambiguity
0.011990
Boolean Closure and Unambiguity of Rational Sets · ICALP 1990

Methods — techniques the papers use, named apart from their topics

probabilistic construction · 0.1coin-flip simulation · 0.1
YearPublicationVenuePosition
2011 On Buffon Machines and Numbers
abstract
The well-know needle experiment of Buffon can be regarded as an analog (i.e., continuous) device that stochastically “computes” the number 2/π ≐ 0.63661, which is the experiment's probability of success. Generalizing the experiment and simplifying the computational framework, we consider probability distributions, which can be produced perfectly, from a discrete source of unbiased coin flips. We describe and analyse a few simple Buffon machines that generate geometric, Poisson, and logarithmic-series distributions. We provide human-accessible Buffon machines, which require a dozen coin flips or less, on average, and produce experiments whose probabilities of success are expressible in terms of numbers such as . Generally, we develop a collection of constructions based on simple probabilistic mechanisms that enable one to design Buffon experiments involving compositions of exponentials and logarithms, polylogarithms, direct and inverse trigonometric functions, algebraic and hypergeometric functions, as well as functions defined by integrals, such as the Gaussian error function.
Philippe Flajolet, Maryse Pelletier, Michèle Soria
SODA2
1999 On the Representation of Finite Deterministic 2-Tape Automata
Maryse Pelletier, Jacques Sakarovitch
Theor. Comput. Sci.1
1990 Boolean Closure and Unambiguity of Rational Sets
Maryse Pelletier
ICALP1
1990 Easy Multiplications II. Extensions of Rational Semigroups
Maryse Pelletier, Jacques Sakarovitch
Inf. Comput.1