Levente Kocsis - ODT Personal data sheet


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Personal data sheet

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VALIDITY EXPIRED
personal data approved: 2015. IX. 14.

Personal data

name	Levente Kocsis
name of institution	Eötvös Loránd University, Budapest
doctoral school	ELTE Doctoral School of Informatics (Academic staff member Az oktató a doktori iskola doktoranduszai számára oktat tantárgyat, és/vagy a doktori iskola megszavazta, hogy doktoranduszok számára kutatási témát írjon ki. )
the share of work in the different doctoral schools.	ELTE Doctoral School of Informatics 100%

Contact details
E-mail address	kocsis.leventesztaki.mta.hu
phone number	+36 1 279-6172

Academic title
scientific degree, title	Ph.D.
year degree was obtained	2003
discipline to which degree belongs	mathematics and computing
institution granting the degree	Universiteit Maastricht, The Netherlands

Employment
2002 -	MTA SZTAKI (research institute, not university) other (not specified) (tudományos főmunkatárs)

Thesis topic supervisor
number of doctoral students supervised until now	0.5
number of students who fulfilled course requirements	0
students who obtained their degrees:

Research
research area	General interest in Machine Learning, Stochastic Optimization, and Games, with focus on Reinforcement Learning, Learning to Rank, and Collaborative Filtering
research field in which current research is conducted	computer sciences

Publications

2014

Hegedűs I, Jelasity M, Kocsis L, Benczúr A: Fully Distributed Robust Singular Value Decomposition, In: Szerk.: [S n ] 14th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P. Los Alamitos: IEEE Press, 2014. Paper 5. 9 p.
type of document: Part of book/Proceedings Paper
language: English
URL

2014

Pálovics R, Benczúr A A, Kocsis L, Kiss T, Frigó E: Exploiting temporal influence in online recommendation, In: Szerk.: [S n ] Proceedings of the 8th ACM Conference on Recommender systems - RECSYS 2014. New York: ACM Press, 2014. pp. 273-280.
type of document: Part of book/Proceedings Paper
language: English
URL

2013

Kocsis L, György A, N. Bán A: BoostingTree: parallel selection of weak learners in boosting, with application to ranking, MACHINE LEARNING 93: (2-3) pp. 293-320.
type of document: Journal paper/Article
language: English
URL

2012

Gelly S, Kocsis L, Schoenauer M, Sebag M, Silver D, Szepesvári C, Teytaud O: The grand challenge of computer go: Monte Carlo tree search and extensions, COMMUNICATIONS OF THE ACM 55: (3) pp. 106-113.
type of document: Journal paper/Article
number of independent citations: 19
language: English
DOI

2011

György A, Kocsis L: Efficient multi-start strategies for local search algorithms, JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH 41: pp. 407-444.
type of document: Journal paper/Article
number of independent citations: 3
language: English

2010

Kocsis L, György A: Fraud detection by generating positive samples for classification from unlabeled data, In: Proceedings of ICML Workshop on Machine Learning and Games.Haifa, Izrael, 2010.06.25 pp. 1-6. Kiadvány: 2010.
type of document: Conference paper/Előadás vagy poszter cikke
number of independent citations: 1
language: English
Full text

2009

Kocsis L, György A: Efficient multi-start strategies for local search algorithms., LECTURE NOTES IN COMPUTER SCIENCE 5781: pp. 705-720.
type of document: Journal paper/Article
number of independent citations: 1
language: English

2007

György A, Kocsis L, Szabó I, Szepesvári C: Continuous time associative bandit problems., In: ICJAI 2007. 20th international joint conference on artificial intelligence.Hyderabad, India, 2007 Hyderabad: IJCAI, pp. 830-835. Kiadvány: Hyderabad: IJCAI, 2007.
type of document: Conference paper/Előadás vagy poszter cikke
number of independent citations: 2
language: English

2006

Kocsis L, Szepesvári C: Universal parameter Optimisation in games based on SPSA, MACHINE LEARNING 63: (3) pp. 249-286.
type of document: Journal paper/Article
number of independent citations: 8
language: English

2006

Kocsis L, Szepesvári C: Bandit based Monte-Carlo planning, LECTURE NOTES IN ARTIFICIAL INTELLIGENCE 4212: pp. 282-293.
type of document: Journal paper/Article
number of independent citations: 444
language: English

Number of independent citations to these publications:

478

Scientometric data

list of publications and citations

number of scientific publications that meet accreditation criteria:

number of scientific publications:

monographs and professional books:

monographs/books in which chapters/sections were contributed:

number of independent citations to scientific publications and creative works:

498