TAPEASE

Theory and Practice of Advanced Search and Enumeration

 Coordinatore AALTO-KORKEAKOULUSAATIO 

Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.

 Nazionalità Coordinatore Finland [FI]
 Totale costo 1˙145˙078 €
 EC contributo 1˙145˙078 €
 Programma FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call ERC-2013-StG
 Funding Scheme ERC-SG
 Anno di inizio 2014
 Periodo (anno-mese-giorno) 2014-02-01   -   2019-01-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    AALTO-KORKEAKOULUSAATIO

 Organization address address: OTAKAARI 1
city: ESPOO
postcode: 2150

contact info
Titolo: Dr.
Nome: Petteri Samuel
Cognome: Kaski
Email: send email
Telefono: +358 50 4300948
Fax: +358 9 8550114

FI (ESPOO) hostInstitution 1˙145˙078.00
2    AALTO-KORKEAKOULUSAATIO

 Organization address address: OTAKAARI 1
city: ESPOO
postcode: 2150

contact info
Titolo: Prof.
Nome: Orponen
Cognome: Pekka
Email: send email
Telefono: +358 500 819491
Fax: +358 9 8550114

FI (ESPOO) hostInstitution 1˙145˙078.00

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 Word cloud

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search    matrix    spaces    algebraic    fastest    rely    multiplication    problem    techniques    algorithms    combinatorial    hard    canonical   

 Obiettivo del progetto (Objective)

'Computer science is permeated with canonical hard problems that, a priori, have a fundamentally combinatorial structure, such as the graph coloring problem, the Steiner tree problem, the Hamiltonian cycle problem, the k-clique problem, and so forth. Accordingly, it would perhaps be quite reasonable to expect that currently the asymptotically fastest solution techniques would rely on the canonical combinatorial algorithms toolbox, such as carefully tailored combinatorial (backtrack/branching) search and case-by-case analysis, combined with, say, advanced data structures. However, this is not the case.

Indeed, currently the fastest known exact/parameterized algorithms for each of the aforementioned problems (and beyond) rely on a mixed bag of advanced _algebraic_ techniques ranging from fast matrix multiplication to sieving e.g. via Möbius inversion and polynomial identity testing. This, in essence, signals that the development of systematic algorithmic principles and tools to cope with exponential-sized combinatorial spaces associated with hard search and enumeration problems is rather in its infancy. The proposed project aims to improve our understanding how such spaces can be systematically transformed and filtered using advanced algebraic and combinatorial techniques. The results of the project are of foremost interest in fundamental research in improving our understanding of computation, but potential exists also for breakthroughs that affect the computing practice, for example in connection with specific canonical tasks such as matrix multiplication or frontier applications such as motif problems in bioinformatics.'

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