Prof. Vladimir Estivill-Castro
Universitat Pompeu Fabra (UPF)
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Academic Career Length
38Years (1989-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 December 1992 in ACM Computing Surveys
Journal Article
Vladimir Estivill-CastroDWDerick Wood
Derick Wood
The design and analysis of adaptive sorting algorithms has made important contributions to both theory and practice. The main contributions from the theoretical point of view are: the description of the complexity of a sorting algorithm not only in terms of the size of a problem instance but also in terms of the disorder of the given problem instance; the establishment of new relationships among measures of disorder; the introduction of new sorting algorithms that take advantage of the existing order in the input sequence; and, the proofs that several of the new sorting algorithms achieve maximal (optimal) adaptivity with respect to several measures of disorder. The main contributions from the practical point of view are: the demonstration that several algorithms currently in use are adaptive; and, the development of new algorithms, similar to currently used algorithms that perform competitively on random sequences and are significantly faster on nearly sorted sequences. In this survey, we present the basic notions and concepts of adaptive sorting and the state of the art of adaptive sorting algorithms.
1 April 2003 in Electronic Notes in Theoretical Computer Science
Journal Article
RDRodney G. Downey
Rodney G. Downey
Vladimir Estivill-CastroMFMichael Fellows
Michael FellowsEPElena Prieto
Elena PrietoFRFrances A. Rosamund
Frances A. Rosamund
The Graph k-Cut problem is that of finding a set of edges of minimum total weight, in an edge-weighted graph, such that their removal from the graph results in a graph having at least k connected components. An algorithm with a running time of O(nk2) for this problem has been known since 1988, due to Goldschmidt and Hochbaum. We show that the problem is hard for the parameterized complexity class W[1]. We also investigate the complexity of a related problem, Cutting A Few Vertices from a Graph, that asks for the minimum cost of separating at least k vertices from an edge-weighted connected graph. We show that this problem also is hard for W[1]
1 July 1998 in International Journal of Geographical Information Science
Journal Article
AMAlan T Murray
Alan T MurrayVladimir Estivill-CastroThis paper reviews approaches for automated pattern spotting and knowledge discovery in spatially referenced data. This is an emerging field which to date has received developmental contributions primarily from researchers in statistics and knowledge discovery in databases (KDD). The field of geographical information systems (GIS) has, however, recognized its importance as a means for providing more exploratory analysis functionality. Tools based upon automated approaches that identify potentially important relationships in spatial data are essential in GIS in order to effectively deal with the increasing amounts of information being gathered. Clustering techniques are proving to be valuable, but there appears to be a general lack of understanding associated with the use and application of various clustering methods in the geographic domain. Further, there is little if any recognition of the relationships between clustering methods. As a result, the development of techniques known to be problematic or inferior has occurred. This paper presents an overview of clustering methods for exploratory spatial data analysis and associated application issues.
24 October 2015 in International Journal of Social Robotics
Journal Article
Wendy MoyleCJCindy Jones
Cindy JonesBSBilly Sung
Billy SungMBMarguerite Bramble
Marguerite BrambleSOSiobhan O'Dwyer
Siobhan O'DwyerVladimir Estivill-Castro +1
1 January 2018 in Expert Systems with Applications
Journal Article
ZIZahidul Islam
Zahidul IslamVladimir Estivill-Castro
Md Anisur RahmanTBTerry Bossomaier
Terry Bossomaier
1 July 2002 in Computers, Environment and Urban Systems
Journal Article
Vladimir Estivill-Castro
Ickjai LeeAbout Me
For over 25 years,Vladimir Estivill-Castro’s consultancy expertise has focused on Machine Learning, Database Efficiency, and Object-Oriented Technologies. Vlad has lead projects in Australia, Canada, Latin-America, Spain and the USA securing over AUD$1MM in competitive research funding. He has delivered invited presentation to industry as well as keynote lectures at international technical conferences. Vlad is co-editor in chief of the series Conferences in Research and Practice in Information Technology and member of the editorial board of Security and Privacy Wiley (ISSN: 2475-6725). He directs Mi-Pal (the Machine Intelligence and Pattern Analysis Laboratory), participating at RoboCup’s Standard Platform League (11 times) and RoboCup@Home (twice). He has supervised several PhD, master and honours projects, earning the best supervision award in 2010 by the Australian Teaching and Learning Council. He has strong skills in computer programming, design of software architectures, image segmentation methods and robots programming. He developed algorithms for efficiently processing the vision and object recognition pipeline for robotic soccer as well as dance and interaction robotic routines for marketing.