Citation Relationships



Sha F, Lin Y, Saul LK, Lee DD (2007) Multiplicative updates for nonnegative quadratic programming. Neural Comput 19:2004-31 [PubMed]

References and models cited by this paper

References and models that cite this paper

Allen JB, Berkley DA (1979) Image method for efficiently simulating small room acoustics J Acoust Soc Am 65:943-950

Bauer E, Koller D, Singer Y (1997) Update rules for parameter estimation in Bayesian networks Proc 13th Ann Conf Uncertainty AI :3-13

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

Cristianini N, Shawe-taylor J (2000) An introduction to support vector machines

Darroch JN, Ratcliff D (1972) Generalized iterative scaling for log-linear models Ann Math Stat 43:1470-1480

Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc B 39:1-38

Diego JM, Tegmark M, Protopapas P, Sandvik HB (2007) Combined reconstruction of weak and strong lensing data with WSLAP Month Not Royal Astro Soc 375:958-970

Friess T, Cristianini N, Campbell C (1998) The kernel adatron algorithm:A fast and simple learning procedure for support vector machine Proc. 15th International Conference on Machine Learning

Kivinen J, Warmuth MK (1997) Exponentiated gradient versus gradient descent for linear predictors Information And Computation 132:1-64

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

Lin Y, Lee DD, Saul LK (2004) Nonnegative deconvolution for time of arrival estimation Proc Intl Conf Speech, Acoustics, Signal Process 2:377-380

Platt J (1999) Fast training of support vector machines using sequential minimal optimization Advances in kernel methods: Support vector learning, Scholkopf B:Burges CJC:Smola AJ, ed. pp.185

Saul LK, Sha F, Lee DD (2003) Statistical signal processing with nonnegativity constraints Proc 8th Euro Conf Speech Communication and Technology 2:1001-1004

Scholkopf B, Sung K, Burges C, Girosi F, Niyogi P, Poggio T, Vapnik V (1997) Comparing support vector machines with gaussian kernels to radial basis function classiers IEEE Trans Signal Process 45:2758-2765

Serafini T, Zanghirati G, Zanni L (2005) Gradient projection methods for quadratic programs and applications in training support vector machines Optimization Methods And Software 20:353-378

Sha F, Saul LK, Lee DD (2003) Multiplicative updates for large margin classifiers Proc 16th Ann Conf Comput Learn Theory :188-202

Sha F, Saul LK, Lee DD (2003) Multiplicative updates for nonnegative quadratic programming in support vector machines Advances in Neural Information Processing Systems 15 (Proceedings of NIPS02), Becker S:Thrun S:Obermayer K, ed. pp.1041

Vapnik V (1998) Statistical Learning Theory

Wright SJ (1997) Primal-dual interior point methods

Zangwill WJ (1969) Nonlinear programming: A unified approach

(21 refs)