BibSLEIGH — Volker

Travelled to:

1 × Australia
1 × Austria
1 × Chile
1 × Egypt
1 × France
1 × Ireland
1 × Italy
1 × Korea
1 × Norway
2 × Canada
3 × China
5 × USA

Collaborated with:

G.M.Lohman P.J.Haas M.Heimel K.Tzoumas S.Ewen V.Raman S.Schelter A.Alexandrov D.E.Simmen W.Han M.Kandil A.Aboulnaga C.Boden U.Jugel Z.Jerzak G.Hackenbroich ∅ F.Hueske M.Schubotz H.Kache I.F.Ilyas H.Pirahesh M.Saecker M.Kutsch T.M.Tran N.Megiddo M.Kiefer D.Warneke M.Altinel A.Singh P.Brown I.Popivanov F.Ramsak R.Fenk K.Elhardt R.Bayer A.Katsifodimos A.Youssef H.S.Cohl M.Kaufmann M.Stillger O.Kao M.Schenck H.Pirk S.Manegold S.Padmanabhan W.Kwak J.Lee J.Ng P.G.Brown S.Breß B.Kocher G.Saake U.Srivastava M.Zirkel M.Schwarzer N.Meuschke C.Breitinger B.Gipp S.Dudoladov C.Xu T.Karnagel M.Hille M.Ludwig D.Habich W.Lehner M.Vrhovnik H.Schwarz O.Suhre B.Mitschang A.Maier T.Kraft A.Lerner D.C.Zilio S.Lightstone A.Kunft F.Schüler L.Thamsen T.Herb D.Battré E.Nijkamp N.Karayannidis A.Tsois T.K.Sellis R.Pieringer S.Cline R.Kartha E.Louie L.Mau Y.Ng

Talks about:

data (12) optim (8) process (7) queri (7) parallel (6) progress (4) action (4) statist (3) estim (3) iter (3)

Person: Volker Markl

DBLP: Markl:Volker

Contributed to:

2015

2014

2013

2012

2010

2008

2007

2006

2005

2004

2002

2001

2000

2016

Wrote 36 papers:

SIGIR-2015-SchubotzYMC #challenge #information retrieval #wiki: Challenges of Mathematical Information Retrievalin the NTCIR-11 Math Wikipedia Task (MS, AY, VM, HSC), pp. 951–954.
SIGMOD-2015-AlexandrovKKSTK #parallel: Implicit Parallelism through Deep Language Embedding (AA, AK, AK, FS, LT, OK, TH, VM), pp. 47–61.
SIGMOD-2015-DudoladovXSKETM: Optimistic Recovery for Iterative Dataflows in Action (SD, CX, SS, AK, SE, KT, VM), pp. 1439–1443.
SIGMOD-2015-HeimelKM #estimation #kernel #modelling #multi #self: Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation (MH, MK, VM), pp. 1477–1492.
SIGMOD-2014-KarnagelHLHLHM #performance #query: Demonstrating efficient query processing in heterogeneous environments (TK, MH, ML, DH, WL, MH, VM), pp. 693–696.
VLDB-2014-BressHSKMS #hardware #named: Ocelot/HyPE: Optimized Data Processing on Heterogeneous Hardware (SB, MH, MS, BK, VM, GS), pp. 1609–1612.
VLDB-2014-JugelJHM #performance #visual notation: Faster Visual Analytics through Pixel-Perfect Aggregation (UJ, ZJ, GH, VM), pp. 1705–1708.
VLDB-2014-JugelJM #named #visualisation: M4: A Visualization-Oriented Time Series Data Aggregation (UJ, ZJ, GH, VM), pp. 797–808.
VLDB-2014-Markl #big data #data analysis #declarative #independence: Breaking the Chains: On Declarative Data Analysis and Data Independence in the Big Data Era (VM), pp. 1730–1733.
RecSys-2013-SchelterBSAM #distributed #matrix #pipes and filters #using: Distributed matrix factorization with mapreduce using a series of broadcast-joins (SS, CB, MS, AA, VM), pp. 281–284.
SIGMOD-2013-EwenSTWM #parallel: Iterative parallel data processing with stratosphere: an inside look (SE, SS, KT, DW, VM), pp. 1053–1056.
VLDB-2013-HeimelSPMM #in memory #parallel: Hardware-Oblivious Parallelism for In-Memory Column-Stores (MH, MS, HP, SM, VM), pp. 709–720.
RecSys-2012-SchelterBM #pipes and filters #scalability #similarity: Scalable similarity-based neighborhood methods with MapReduce (SS, CB, VM), pp. 163–170.
VLDB-2012-AlexandrovTM #generative #named #scalability: Myriad: Scalable and Expressive Data Generation (AA, KT, VM), pp. 1890–1893.
VLDB-2012-EwenTKM #data flow #performance: Spinning Fast Iterative Data Flows (SE, KT, MK, VM), pp. 1268–1279.
VLDB-2010-AlexandrovBEHHKMNW #data analysis #parallel: Massively Parallel Data Analysis with PACTs on Nephele (AA, DB, SE, MH, FH, OK, VM, EN, DW), pp. 1625–1628.
SIGMOD-2008-SimmenAMPS #intranet #named: Damia: data mashups for intranet applications (DES, MA, VM, SP, AS), pp. 1171–1182.
VLDB-2008-HanKLLM #optimisation #query: Parallelizing query optimization (WSH, WK, JL, GML, VM), pp. 188–200.
SIGMOD-2007-HanNMKK #database #optimisation #parallel: Progressive optimization in a shared-nothing parallel database (WSH, JN, VM, HK, MK), pp. 809–820.
VLDB-2007-AltinelBCKLMMNSS #intranet #named: DAMIA — A Data Mashup Fabric for Intranet Applications (MA, PB, SC, RK, EL, VM, LM, YHN, DES, AS), pp. 1370–1373.
VLDB-2007-HaasHM #dependence #detection #feedback #query: Detecting Attribute Dependencies from Query Feedback (PJH, FH, VM), pp. 830–841.
VLDB-2007-VrhovnikSSMMMK #approach #process: An Approach to Optimize Data Processing in Business Processes (MV, HS, OS, BM, VM, AM, TK), pp. 615–626.
SIGMOD-2006-MarklKTHM #consistency #estimation #named: MAXENT: consistent cardinality estimation in action (VM, MK, TMT, PJH, NM), pp. 775–777.
VLDB-2006-KacheHMRE #named #optimisation #query: POP/FED: Progressive Query Optimization for Federated Queries in DB2 (HK, WSH, VM, VR, SE), pp. 1175–1178.
SIGMOD-2005-HaasKLMPRZ #automation #statistics: Automated statistics collection in action (PJH, MK, AL, VM, IP, VR, DCZ), pp. 933–935.
VLDB-2005-MarklMKTHS: Consistently Estimating the Selectivity of Conjuncts of Predicates (VM, NM, MK, TMT, PJH, US), pp. 373–384.
SIGMOD-2004-IlyasMHBA #automation #correlation #dependence #functional #named: CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies (IFI, VM, PJH, PB, AA), pp. 647–658.
SIGMOD-2004-MarklRSLP #optimisation #query #robust: Robust Query Processing through Progressive Optimization (VM, VR, DES, GML, HP), pp. 659–670.
VLDB-2004-AboulnagaHLLMPR #automation #statistics: Automated Statistics Collection in DB2 UDB (AA, PJH, SL, GML, VM, IP, VR), pp. 1146–1157.
VLDB-2004-IlyasMHBA #automation #correlation #generative #named #statistics: CORDS: Automatic Generation of Correlation Statistics in DB2 (IFI, VM, PJH, PGB, AA), pp. 1341–1344.
VLDB-2004-RamanMSLP #optimisation: Progressive Optimization in Action (VR, VM, DES, GML, HP), pp. 1337–1340.
SIGMOD-2002-MarklL #learning: Learning table access cardinalities with LEO (VM, GML), p. 613.
VLDB-2002-KarayannidisTSPMRFEB #clustering #query: Processing Star Queries on Hierarchically-Clustered Fact Tables (NK, AT, TKS, RP, VM, FR, RF, KE, RB), pp. 730–741.
VLDB-2001-StillgerLMK #learning #named: LEO — DB2’s LEarning Optimizer (MS, GML, VM, MK), pp. 19–28.
VLDB-2000-RamsakMFZEB #database #kernel: Integrating the UB-Tree into a Database System Kernel (FR, VM, RF, MZ, KE, RB), pp. 263–272.
JCDL-2016-SchwarzerSMBMG #recommendation #wiki: Evaluating Link-based Recommendations for Wikipedia (MS, MS, NM, CB, VM, BG), pp. 191–200.