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Lin CJ (2007) Projected gradient methods for nonnegative matrix factorization. Neural Comput 19:2756-79 [PubMed]

References and models cited by this paper

References and models that cite this paper

Bertsekas DP (1976) On the Goldstein-Levitin-Polyak gradient projection method IEEE Trans Automatic Control 21:174-184

Bertsekas DP (1999) Nonlinear programming (2nd ed)

Brunet JP (2004) An NMF Program. Available online at http:--www.broad.mit.edu-mpr-publications-projects-NMF-nmf.m

Brunet JP, Tamayo P, Golub TR, Mesirov JP (2004) Metagenes and molecular pattern discovery using matrix factorization. Proc Natl Acad Sci U S A 101:4164-9 [Journal] [PubMed]

Calamai PH, More JJ (1987) Projected gradient methods for linearly constrained problems Mathematical Programming 39:93-116

Chu M, Diele F, Plemmons R, Ragni S (2005) Optimality, computation and interpretation of nonnegative matrix factorizations Available online athttp:--www4.ncsu.edu-mtchu-Research-Papers-nnmf.ps

Donoho D, Stodden V (2004) When does non-negative matrix factorization give a correct decomposition into parts? Advances in neural information processing systems, Thrun S:Saul L:Scholkopf B, ed.

Gonzales EF, Zhang Y (2005) Accelerating the Lee-Seung algorithm for non-negative matrix factorization Tech Rep Department of Computational and Applied Mathematics, Rice University

Grippo L, Sciandrone M (2000) On the convergence of the block nonlinear Gauss-Seidel method under convex constraints Operations Research Letters 26:127-136

Hoyer PO (2002) Non-negative sparse coding Proceedings of IEEE Workshop on Neural Networks for Signal Processing :557-565

Hoyer PO (2004) Non-negative matrix factorization with sparseness constraints J Mach Learn Res 5:1457-1469

Lawson CL, Hanson RJ (1974) Linear least squares with linear inequality constraints Solving least squares problems :161

Lee DD, Seung HS (1999) Learning the parts of objects by non-negative matrix factorization. Nature 401:788-91 [Journal] [PubMed]

Lee DD, Seung HS (2000) Algorithms for non-negative matrix factorization Advances in neural information processing systems, Leen TK:Dietterich TG:Tresp V, ed. pp.556

Lewis DD, Yang Y, Rose TG, Li F (2004) RCV1: A new benchmark collection for text categorization research J Mach Learn Res 5:361-397

Lin CJ (1999) Newtons method for large-scale bound constrained problems SIAM J Optim 9:1100-1127

Mccormick GP, Tapia RA (1972) The gradient projection method under mild differentiability conditions SIAM J Control 10:93-98

Paatero P (1999) The multilinear engine table-driven, least squares program for solving multilinear problems, including the n-way parallel factor analysis model J Comput Graph Stat 8:854-888

Paatero P, Tapper U (1994) Positive matrix factorization: A non-negative factor model with optimal utilization of error Environmetrics 5:111-126

Piper J, Pauca P, Plemmons R, Giffin M (2004) Object characterization from spectral data using nonnegative factorization and information theory Proc AMOS Tech Conf

Powell MJD (1973) On search directions for minimization Mathematical Programming 4:193-201

Shepherd S (2004) Non-negative matrix factorization Available online at http:--www.simonshepherd.supanet.com-nnmf.htm

Xu W, Liu X, Gong Y (2003) Document clustering based on non-negative matrix factorization Proc 26th Ann Intl ACM SIGIR Conf :297-273

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