메뉴 건너뛰기




Volumn , Issue , 2012, Pages 131-140

Efficient pattern-based time series classification on GPU

Author keywords

Classification; GPU; Pattern based classification; Time series

Indexed keywords

DISCOVERY ALGORITHM; DYNAMIC PROGRAMMING ALGORITHM; GPU; GPU IMPLEMENTATION; GPU PROGRAMMING; HIGHLY PARALLELS; INTERPRETABILITY; ITS APPLICATIONS; LARGE DATASETS; PROCESS UNIT; RUNNING TIME; SAMPLE DATASET; TIME SERIES CLASSIFICATIONS;

EID: 84874030981     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2012.132     Document Type: Conference Paper
Times cited : (58)

References (19)
  • 1
    • 81055156693 scopus 로고    scopus 로고
    • A brief survey on sequence classification
    • Z. Xing, J. Pei, and E. Keogh, "A brief survey on sequence classification," SIGKDD Explorations, vol. 12, pp. 40-48, 2010.
    • (2010) SIGKDD Explorations , vol.12 , pp. 40-48
    • Xing, Z.1    Pei, J.2    Keogh, E.3
  • 2
    • 70350660908 scopus 로고    scopus 로고
    • Time series shapelets: A new primitive for data mining
    • L. Ye and E. Keogh, "Time Series Shapelets: A New Primitive for Data Mining," in KDD, 2009.
    • (2009) KDD
    • Ye, L.1    Keogh, E.2
  • 3
    • 80052669927 scopus 로고    scopus 로고
    • Logical-shapelets: An expressive primitive for time series classification
    • A. Mueen, E. Keogh, and N. Young, "Logical-Shapelets: An Expressive Primitive for Time Series Classification," in KDD, 2011, pp. 1154-1162.
    • (2011) KDD , pp. 1154-1162
    • Mueen, A.1    Keogh, E.2    Young, N.3
  • 4
    • 79953779756 scopus 로고    scopus 로고
    • Emerald & Jade ed. Morgan Kaufmann
    • W.-M. W. Hwu, Ed., GPU Computing Gems, Emerald & Jade ed. Morgan Kaufmann, 2011.
    • (2011) GPU Computing Gems
    • Hwu, W.-M.W.1
  • 5
    • 53749089739 scopus 로고    scopus 로고
    • Fast support vector machine training and classification on graphics processors
    • ACM Press
    • B. Catanzaro, N. Sundaram, and K. Keutzer, "Fast support vector machine training and classification on graphics processors," in ICML. ACM Press, 2008, pp. 104-111.
    • (2008) ICML , pp. 104-111
    • Catanzaro, B.1    Sundaram, N.2    Keutzer, K.3
  • 6
    • 80052661286 scopus 로고    scopus 로고
    • A GPU-tailored approach for training kernelized SVMs
    • A. Cotter, N. Srebro, and J. Keshet, "A GPU-tailored approach for training kernelized SVMs," in KDD, 2011.
    • (2011) KDD
    • Cotter, A.1    Srebro, N.2    Keshet, J.3
  • 7
    • 71149105669 scopus 로고    scopus 로고
    • Large-scale deep unsupervised learning using graphics processors
    • ACM
    • R. Raina, A. Madhavan, and A. Ng, "Large-scale deep unsupervised learning using graphics processors," in ICML. ACM, 2009, pp. 873-880.
    • (2009) ICML , pp. 873-880
    • Raina, R.1    Madhavan, A.2    Ng, A.3
  • 8
    • 79955691941 scopus 로고    scopus 로고
    • Parallel inference for latent dirichlet allocation on graphics processing units
    • F. Yan, N. Xu, and Y. A. Qi, "Parallel inference for latent dirichlet allocation on graphics processing units," in NIPS, 2009.
    • (2009) NIPS
    • Yan, F.1    Xu, N.2    Qi, Y.A.3
  • 9
    • 79951752243 scopus 로고    scopus 로고
    • Accelerating dynamic time warping subsequence search with GPUs and FPGAs
    • D. Sart, A. Mueen, W. Najjar, V. Niennattrakul, and E. Keogh, "Accelerating Dynamic Time Warping Subsequence Search with GPUs and FPGAs," in ICDM, 2010.
    • (2010) ICDM
    • Sart, D.1    Mueen, A.2    Najjar, W.3    Niennattrakul, V.4    Keogh, E.5
  • 10
    • 0034592912 scopus 로고    scopus 로고
    • Scaling up dynamic time warping for datamining applications
    • E. J. Keogh and M. J. Pazzani, "Scaling up dynamic time warping for datamining applications," in KDD, 2000, pp. 285-289.
    • (2000) KDD , pp. 285-289
    • Keogh, E.J.1    Pazzani, M.J.2
  • 11
    • 84867136666 scopus 로고    scopus 로고
    • Querying and mining of time series data: Experimental comparison of representations and distance measures
    • H. Ding, G. Trajcevski, P. Scheuermann, X. Wang, and E. Keogh, "Querying and mining of time series data: experimental comparison of representations and distance measures," PVLDB, vol. 1, pp. 1542-1552, 2008. [Online]. Available: http://dx.doi.org/10.1145/1454159.1454226
    • (2008) PVLDB , vol.1 , pp. 1542-1552
    • Ding, H.1    Trajcevski, G.2    Scheuermann, P.3    Wang, X.4    Keogh, E.5
  • 12
    • 84866041459 scopus 로고    scopus 로고
    • A complexity-invariant distance measure for time series
    • G. E. A. P. A. Batista, X. Wang, and E. J. Keogh, "A complexity-invariant distance measure for time series," in SDM, 2011.
    • (2011) SDM
    • Batista, G.E.A.P.A.1    Wang, X.2    Keogh, E.J.3
  • 14
    • 70449595775 scopus 로고    scopus 로고
    • Program optimization of stencil based application on the GPU-accelerated system
    • G. Wang, X. Yang, Y. Zhang, T. Tang, and X. Fan, "Program Optimization of Stencil Based Application on the GPU-Accelerated System," in ISPA, 2009, pp. 219-225.
    • (2009) ISPA , pp. 219-225
    • Wang, G.1    Yang, X.2    Zhang, Y.3    Tang, T.4    Fan, X.5
  • 17
    • 52649163329 scopus 로고    scopus 로고
    • Direct discriminative pattern mining for effective classification
    • H. Cheng, X. Yan, J. Han, and P. S. Yu, "Direct discriminative pattern mining for effective classification," in ICDE, 2008.
    • (2008) ICDE
    • Cheng, H.1    Yan, X.2    Han, J.3    Yu, P.S.4
  • 18
    • 65449142148 scopus 로고    scopus 로고
    • Partial least squares regression for graph mining
    • H. Saigo, N. Krämer, and K. Tsuda, "Partial least squares regression for graph mining," in KDD, 2008.
    • (2008) KDD
    • Saigo, H.1    Krämer, N.2    Tsuda, K.3
  • 19
    • 69449099775 scopus 로고    scopus 로고
    • Classification of software behaviors for failure detection: A discriminative pattern mining approach
    • D. Lo, H. Cheng, J. Han, S.-C. Khoo, and C. Sun, "Classification of software behaviors for failure detection: A discriminative pattern mining approach," in KDD, 2009.
    • (2009) KDD
    • Lo, D.1    Cheng, H.2    Han, J.3    Khoo, S.-C.4    Sun, C.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.