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Volumn 2015-May, Issue , 2015, Pages 1969-1984

Learning generalized linear models over normalized data

Author keywords

Analytics; Feature engineering; Joins; Machine learning

Indexed keywords

ARTIFICIAL INTELLIGENCE; INFORMATION MANAGEMENT; JOINING; LEARNING SYSTEMS; REDUNDANCY;

EID: 84957595566     PISSN: 07308078     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2723372.2723713     Document Type: Conference Paper
Times cited : (134)

References (34)
  • 3
    • 84957580141 scopus 로고    scopus 로고
    • IBM Report. www-01.ibm.com/software/data/bigdata/.
    • IBM Report1
  • 6
    • 84899845537 scopus 로고    scopus 로고
    • A reliable effective terascale linear learning system
    • A. Agarwal et al. A Reliable Effective Terascale Linear Learning System. JMLR, 15:1111-1133, 2014.
    • (2014) JMLR , vol.15 , pp. 1111-1133
    • Agarwal, A.1
  • 7
    • 85084012304 scopus 로고    scopus 로고
    • Brainwash: A data system for feature engineering
    • M. Anderson et al. Brainwash: A Data System for Feature Engineering. In CIDR, 2013.
    • (2013) CIDR
    • Anderson, M.1
  • 8
    • 84891100919 scopus 로고    scopus 로고
    • Aggregation and ordering in factorised databases
    • N. Bakibayev et al. Aggregation and Ordering in Factorised Databases. In VLDB, 2013.
    • (2013) VLDB
    • Bakibayev, N.1
  • 9
    • 84880568698 scopus 로고    scopus 로고
    • Simulation of database-valued markov chains using SimSQL
    • Z. Cai et al. Simulation of Database-valued Markov Chains Using SimSQL. In SIGMOD, 2013.
    • (2013) SIGMOD
    • Cai, Z.1
  • 10
    • 0008753064 scopus 로고
    • Including group-by in query optimization
    • S. Chaudhuri and K. Shim. Including Group-By in Query Optimization. In VLDB, 1994.
    • (1994) VLDB
    • Chaudhuri, S.1    Shim, K.2
  • 11
    • 0001366593 scopus 로고
    • Discrete-variable extremum problems
    • G. B. Dantzig. Discrete-Variable Extremum Problems. Operations Research, 5(2): pp. 266-277, 1957.
    • (1957) Operations Research , vol.5 , Issue.2 , pp. 266-277
    • Dantzig, G.B.1
  • 12
    • 77954751910 scopus 로고    scopus 로고
    • Ricardo: Integrating R and hadoop
    • S. Das et al. Ricardo: Integrating R and Hadoop. In SIGMOD, 2010.
    • (2010) SIGMOD
    • Das, S.1
  • 13
    • 84862644049 scopus 로고    scopus 로고
    • Towards a unified architecture for in-RDBMS analytics
    • X. Feng, A. Kumar, B. Recht, and C. Ré. Towards a Unified Architecture for in-RDBMS Analytics. In SIGMOD, 2012.
    • (2012) SIGMOD
    • Feng, X.1    Kumar, A.2    Recht, B.3    Ré, C.4
  • 15
    • 79957859069 scopus 로고    scopus 로고
    • SystemML: Declarative machine learning on mapreduce
    • A. Ghoting et al. SystemML: Declarative Machine Learning on MapReduce. In ICDE, 2011.
    • (2011) ICDE
    • Ghoting, A.1
  • 16
    • 21744433274 scopus 로고    scopus 로고
    • Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals
    • Jan.
    • J. Gray et al. Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals. Data Min. Knowl. Discov., 1(1):29-53, Jan. 1997.
    • (1997) Data Min. Knowl. Discov. , vol.1 , Issue.1 , pp. 29-53
    • Gray, J.1
  • 18
    • 84873199454 scopus 로고    scopus 로고
    • The MADlib analytics library or MAD skills, the SQL
    • J. Hellerstein et al. The MADlib Analytics Library or MAD Skills, the SQL. In VLDB, 2012.
    • (2012) VLDB
    • Hellerstein, J.1
  • 19
    • 84863557037 scopus 로고    scopus 로고
    • Incrementally maintaining classification using an RDBMS
    • M. L. Koc and C. Ré. Incrementally Maintaining Classification using an RDBMS. In VLDB, 2011.
    • (2011) VLDB
    • Koc, M.L.1    Ré, C.2
  • 20
    • 84891085706 scopus 로고    scopus 로고
    • Feature selection in enterprise analytics: A demonstration using an R-based data analytics system
    • P. Konda, A. Kumar, C. Ré, and V. Sashikanth. Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System. In VLDB, 2013.
    • (2013) VLDB
    • Konda, P.1    Kumar, A.2    Ré, C.3    Sashikanth, V.4
  • 21
    • 85084017339 scopus 로고    scopus 로고
    • MLbase: A distributed machine-learning system
    • T. Kraska et al. MLbase: A Distributed Machine-learning System. In CIDR, 2013.
    • (2013) CIDR
    • Kraska, T.1
  • 22
    • 84875277978 scopus 로고    scopus 로고
    • Hazy: Making it easier to build and maintain big-data analytics
    • March 2013
    • A. Kumar et al. Hazy: Making it Easier to Build and Maintain Big-data Analytics. CACM, 56(3):40-49, March 2013.
    • CACM , vol.56 , Issue.3 , pp. 40-49
    • Kumar, A.1
  • 23
    • 80053161467 scopus 로고    scopus 로고
    • GraphLab: A new framework for parallel machine learning
    • Y. Low et al. GraphLab: A New Framework For Parallel Machine Learning. In UAI, 2010.
    • (2010) UAI
    • Low, Y.1
  • 25
    • 84904351018 scopus 로고    scopus 로고
    • LINVIEW: Incremental view maintenance for complex analytical queries
    • M. Nikolic et al. LINVIEW: Incremental View Maintenance for Complex Analytical Queries. In SIGMOD, 2014.
    • (2014) SIGMOD
    • Nikolic, M.1
  • 28
    • 84881117508 scopus 로고    scopus 로고
    • Scaling factorization machines to relational data
    • S. Rendle. Scaling Factorization Machines to Relational Data. In VLDB, 2013.
    • (2013) VLDB
    • Rendle, S.1
  • 29
    • 85051567368 scopus 로고
    • Access path selection in a relational database management system
    • P. G. Selinger et al. Access Path Selection in a Relational Database Management System. In SIGMOD, 1979.
    • (1979) SIGMOD
    • Selinger, P.G.1
  • 30
    • 0023977778 scopus 로고
    • Multiple-query optimization
    • Mar.
    • T. K. Sellis. Multiple-Query Optimization. ACM TODS, 13(1):23-52, Mar. 1988.
    • (1988) ACM TODS , vol.13 , Issue.1 , pp. 23-52
    • Sellis, T.K.1
  • 31
    • 84976660052 scopus 로고
    • Join processing in database systems with large main memories
    • Aug.
    • L. D. Shapiro. Join Processing in Database Systems with Large Main Memories. ACM TODS, 11(3):239-264, Aug. 1986.
    • (1986) ACM TODS , vol.11 , Issue.3 , pp. 239-264
    • Shapiro, L.D.1
  • 32
    • 0003142704 scopus 로고
    • Eager aggregation and lazy aggregation
    • W. P. Yan and P.-Å. Larson. Eager Aggregation and Lazy Aggregation. In VLDB, 1995.
    • (1995) VLDB
    • Yan, W.P.1    Larson, P.-Å.2
  • 33
    • 84904317928 scopus 로고    scopus 로고
    • Materialization optimizations for feature selection workloads
    • C. Zhang, A. Kumar, and C. Ré. Materialization Optimizations for Feature Selection Workloads. In SIGMOD, 2014.
    • (2014) SIGMOD
    • Zhang, C.1    Kumar, A.2    Ré, C.3
  • 34
    • 77952773120 scopus 로고    scopus 로고
    • I/O-efficient statistical computing with RIOT
    • Y. Zhang, W. Zhang, and J. Yang. I/O-Efficient Statistical Computing with RIOT. In ICDE, 2010.
    • (2010) ICDE
    • Zhang, Y.1    Zhang, W.2    Yang, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.