Travelled to:
1 × Canada
1 × France
1 × Germany
1 × Korea
1 × Spain
1 × United Kingdom
3 × USA
Collaborated with:
M.W.Mahoney Y.Makris C.Boutsidis M.Maggioni S.Almukhaizim K.Akcoglu M.Kao I.Kerenidis P.Raghavan M.Magdon-Ismail D.P.Woodruff A.Dasgupta B.Harb V.Josifovski
Talks about:
concurr (2) tensor (2) select (2) featur (2) detect (2) error (2) fsms (2) fast (2) data (2) unsupervis (1)
Person: Petros Drineas
DBLP: Drineas:Petros
Contributed to:
Wrote 9 papers:
- ICML-2012-MahoneyDMW #approximate #matrix #performance #statistics
- Fast approximation of matrix coherence and statistical leverage (MWM, PD, MMI, DPW), p. 137.
- KDD-2008-BoutsidisMD #analysis #component #feature model
- Unsupervised feature selection for principal components analysis (CB, MWM, PD), pp. 61–69.
- KDD-2007-DasguptaDHJM #classification #feature model
- Feature selection methods for text classification (AD, PD, BH, VJ, MWM), pp. 230–239.
- KDD-2006-MahoneyMD
- Tensor-CUR decompositions for tensor-based data (MWM, MM, PD), pp. 327–336.
- VLDB-2006-DrineasM #algorithm #matrix #random #set
- Randomized Algorithms for Matrices and Massive Data Sets (PD, MWM), p. 1269.
- DATE-v1-2004-AlmukhaizimDM #bound #concurrent #detection #fault #latency #on the
- On Concurrent Error Detection with Bounded Latency in FSMs (SA, PD, YM), pp. 596–603.
- DATE-2003-DrineasM #concurrent #detection #fault #monitoring
- Non-Intrusive Concurrent Error Detection in FSMs through State/Output Compaction and Monitoring via Parity Trees (PD, YM), pp. 11164–11167.
- ICALP-2002-AkcogluDK #performance
- Fast Universalization of Investment Strategies with Provably Good Relative Returns (KA, PD, MYK), pp. 888–900.
- STOC-2002-DrineasKR #recommendation
- Competitive recommendation systems (PD, IK, PR), pp. 82–90.