메뉴 건너뛰기




Volumn 6913 LNAI, Issue PART 3, 2011, Pages 305-317

Fast projections onto ℓ1,q-norm balls for grouped feature selection

Author keywords

[No Author keywords available]

Indexed keywords

EFFICIENT ALGORITHM; JOINT SPARSITY; NUMERICAL RESULTS; REGRESSION PROBLEM; SCALABLE METHODS; STANDARD METHOD; THREE ORDERS OF MAGNITUDE;

EID: 80052405487     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23808-6_20     Document Type: Conference Paper
Times cited : (35)

References (39)
  • 1
    • 85162027958 scopus 로고    scopus 로고
    • Structured sparsity-inducing norms through submodular functions
    • Bach, F.: Structured sparsity-inducing norms through submodular functions. In: NIPS (2010)
    • (2010) NIPS
    • Bach, F.1
  • 2
    • 80052253522 scopus 로고    scopus 로고
    • Convex optimization with sparsity-inducing norms
    • Sra, S., Nowozin, S., Wright, S.J. (eds.) MIT Press, Cambridge
    • Bach, F., Jenatton, R., Mairal, J., Obozinski, G.: Convex optimization with sparsity-inducing norms. In: Sra, S., Nowozin, S., Wright, S.J. (eds.) Optimization for Machine Learning. MIT Press, Cambridge (2011)
    • (2011) Optimization for Machine Learning
    • Bach, F.1    Jenatton, R.2    Mairal, J.3    Obozinski, G.4
  • 3
    • 46249088758 scopus 로고    scopus 로고
    • Consistency of the Group Lasso and Multiple Kernel Learning
    • Bach, F.R.: Consistency of the Group Lasso and Multiple Kernel Learning. J. Mach. Learn. Res. 9, 1179-1225 (2008)
    • (2008) J. Mach. Learn. Res. , vol.9 , pp. 1179-1225
    • Bach, F.R.1
  • 7
    • 0034345420 scopus 로고    scopus 로고
    • Nonmonotone Spectral Projected Gradient Methods on Convex Sets
    • Birgin, E.G., Martínez, J.M., Raydan, M.: Nonmonotone Spectral Projected Gradient Methods on Convex Sets. SIAM J. Opt. 10(4), 1196-1211 (2000)
    • (2000) SIAM J. Opt. , vol.10 , Issue.4 , pp. 1196-1211
    • Birgin, E.G.1    Martínez, J.M.2    Raydan, M.3
  • 9
    • 15544385032 scopus 로고    scopus 로고
    • Projected Barzilai-Borwein Methods for Large-scale Box-constrained Quadratic Programming
    • Dai, Y.H., Fletcher, R.: Projected Barzilai-Borwein Methods for Large-scale Box-constrained Quadratic Programming. Numerische Mathematik 100(1), 21-47 (2005)
    • (2005) Numerische Mathematik , vol.100 , Issue.1 , pp. 21-47
    • Dai, Y.H.1    Fletcher, R.2
  • 10
    • 0029307534 scopus 로고    scopus 로고
    • Denoising by soft-thresholding
    • Donoho, D.: Denoising by soft-thresholding. IEEE Tran. Inf. Theory 41(3), 613-627 (2002)
    • (2002) IEEE Tran. Inf. Theory , vol.41 , Issue.3 , pp. 613-627
    • Donoho, D.1
  • 11
    • 75249102673 scopus 로고    scopus 로고
    • Online and Batch Learning using Forward-Backward Splitting
    • September
    • Duchi, J., Singer, Y.: Online and Batch Learning using Forward-Backward Splitting. JMLR (September 2009)
    • (2009) JMLR
    • Duchi, J.1    Singer, Y.2
  • 13
    • 12244250351 scopus 로고    scopus 로고
    • Regularized multi-task learning
    • Evgeniou, T., Pontil, M.: Regularized multi-task learning. In: KDD (2004)
    • (2004) KDD
    • Evgeniou, T.1    Pontil, M.2
  • 15
    • 77956506018 scopus 로고    scopus 로고
    • Proximal Methods for Sparse Hierarchical Dictionary Learning
    • Jenatton, R., Mairal, J., Obozinski, G., Bach, F.: Proximal Methods for Sparse Hierarchical Dictionary Learning. In: ICML (2010)
    • (2010) ICML
    • Jenatton, R.1    Mairal, J.2    Obozinski, G.3    Bach, F.4
  • 17
    • 36049044098 scopus 로고    scopus 로고
    • On Linear-Time Algorithms for the Continuous Quadratic Knapsack Problem
    • Kiwiel, K.: On Linear-Time Algorithms for the Continuous Quadratic Knapsack Problem. Journal of Optimization Theory and Applications 134, 549-554 (2007)
    • (2007) Journal of Optimization Theory and Applications , vol.134 , pp. 549-554
    • Kiwiel, K.1
  • 19
    • 71149111015 scopus 로고    scopus 로고
    • Blockwise Coordinate Descent Procedures for the Multi-task Lasso, with Applications to Neural Semantic Basis Discovery
    • Liu, H., Palatucci, M., Zhang, J.: Blockwise Coordinate Descent Procedures for the Multi-task Lasso, with Applications to Neural Semantic Basis Discovery. In: Int. Conf. Machine Learning (June 2009)
    • Int. Conf. Machine Learning (June 2009)
    • Liu, H.1    Palatucci, M.2    Zhang, J.3
  • 22
    • 85161968806 scopus 로고    scopus 로고
    • Moreau-Yosida Regularization for Grouped Tree Structure Learning
    • Liu, J., Ye, J.: Moreau-Yosida Regularization for Grouped Tree Structure Learning. In: NIPS (2010)
    • (2010) NIPS
    • Liu, J.1    Ye, J.2
  • 23
    • 71149115443 scopus 로고    scopus 로고
    • Efficient Euclidean projections in linear time
    • June
    • Liu, J., Ye, J.: Efficient Euclidean projections in linear time. In: ICML (June 2009)
    • (2009) ICML
    • Liu, J.1    Ye, J.2
  • 25
    • 0022751477 scopus 로고
    • A finite algorithm for finding the projection of a point onto the canonical simplex of Rn
    • Michelot, C.: A finite algorithm for finding the projection of a point onto the canonical simplex of Rn. J. Optim. Theory Appl. 50(1), 195-200 (1986)
    • (1986) J. Optim. Theory Appl. , vol.50 , Issue.1 , pp. 195-200
    • Michelot, C.1
  • 33
    • 77955995598 scopus 로고    scopus 로고
    • Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm
    • Schmidt, M., Van den Berg, E., Friedlander, M., Murphy, K.: Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm. In: AISTATS (2009)
    • (2009) AISTATS
    • Schmidt, M.1    Van Den Berg, E.2    Friedlander, M.3    Murphy, K.4
  • 34
    • 34548232392 scopus 로고    scopus 로고
    • Input selection and shrinkage in multiresponse linear regression
    • Similä, T., Tikka, J.: Input selection and shrinkage in multiresponse linear regression. Comp. Stat. & Data Analy. 52(1), 406-422 (2007)
    • (2007) Comp. Stat. & Data Analy. , vol.52 , Issue.1 , pp. 406-422
    • Similä, T.1    Tikka, J.2
  • 35
    • 30844461481 scopus 로고    scopus 로고
    • Algorithms for simultaneous sparse approximation, Part II: Convex relaxation
    • Tropp, J.A.: Algorithms for simultaneous sparse approximation, Part II: Convex relaxation. Signal Proc. 86(3), 589-602 (2006)
    • (2006) Signal Proc. , vol.86 , Issue.3 , pp. 589-602
    • Tropp, J.A.1
  • 38
    • 85162027638 scopus 로고    scopus 로고
    • Probabilistic Multi-Task Feature Selection
    • Zhang, Y., Yeung, D.Y., Xu, Q.: Probabilistic Multi-Task Feature Selection. In: NIPS (2010)
    • (2010) NIPS
    • Zhang, Y.1    Yeung, D.Y.2    Xu, Q.3
  • 39
    • 69949155103 scopus 로고    scopus 로고
    • The composite absolute penalties family for grouped and hierarchical variable selection
    • Zhao, P., Rocha, G., Yu, B.: The composite absolute penalties family for grouped and hierarchical variable selection. Ann. Stat. 37(6A), 3468-3497 (2009)
    • (2009) Ann. Stat. , vol.37 , Issue.6 A , pp. 3468-3497
    • Zhao, P.1    Rocha, G.2    Yu, B.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.