pauleve-reports.bib

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@techreport{PMR11-RR-SAAI,
  author = {{P}aulev{\'e}, {L}o{\"i}c and {M}agnin, {M}organ and {R}oux, {O}livier},
  title = { {S}tatic {A}nalysis by {A}bstract {I}nterpretation of {B}iological
	{R}egulatory {N}etworks {D}ynamics},
  institution = {IRCCyN},
  year = {2011},
  type = {Research Report},
  number = {hal-00574353},
  month = mar,
  class = {report},
  url = {http://hal.archives-ouvertes.fr/hal-00574353}
}

@techreport{PMR09-RR-Tuning,
  author = {{P}aulev{\'e}, {L}o{\"i}c and {M}agnin, {M}organ and {R}oux, {O}livier},
  title = {{T}uning {T}emporal {F}eatures within the {S}tochastic $\pi$-{C}alculus},
  institution = {IRCCyN},
  year = {2009},
  type = {Research Report},
  number = {hal-00397308},
  month = jun,
  class = {report},
  timestamp = {2009.06.20},
  url = {http://hal.archives-ouvertes.fr/hal-00397308}
}

@techreport{PMR09-RR-Refining,
  author = {{P}aulev{\'e}, {L}o{\"i}c and {M}agnin, {M}organ and {R}oux, {O}livier},
  title = {{R}efining {D}ynamics of {G}ene {R}egulatory {N}etworks in a {S}tochastic
	$\pi$-{C}alculus {F}ramework},
  institution = {IRCCyN},
  year = {2009},
  type = {Research Report},
  number = {hal-00397235},
  month = jun,
  class = {report},
  timestamp = {2009.06.19},
  url = {http://hal.archives-ouvertes.fr/hal-00397235}
}

@techreport{PauMasterThesis,
  author = {{P}aulev{\'e}, {L}o{\"i}c},
  title = {{E}uclidean lattices for high dimensional indexing and searching},
  institution = {IRISA},
  year = {2008},
  type = {Research Report},
  abstract = {{F}or similarity based searching, multimedia data are represented
	by one or more numerical vectors: we search the nearest neighbors
	of the query. {B}ecause of the huge number of these data and their
	high dimension, classical indexing technics are inefficient. {T}he
	goal of this internship is to study the use of euclidean lattices
	for database indexing. {L}attices have nice properties: they are
	spatial quantizers, thereby generate a partition of the space and
	decoding (quantization step) may be done very quickly. {T}hen, we
	hope to be able to rapidly find a small space region containing data
	similar to a given query point, without reading all the database.},
  affiliation = {{TEXMEX} - {IRISA} - {CNRS}: {UMR}6074 - {INRIA} - {U}niversit{\'e}
	{R}ennes {I} - {I}nstitut {N}ational des {S}ciences {A}ppliqu{\'e}es
	de {R}ennes},
  class = {report},
  keywords = {{E}uclidean lattice, indexing, searching, k nearest neighbors, high
	dimensional space, {S}ift descriptor, permutohedron, nearest faces
	of lattice, k nearest lattice points},
  language = {{F}rench},
  timestamp = {2008.07.01},
  url = {http://hal.inria.fr/inria-00326262}
}