A recurrent neural network solving the approximate nonnegative matrix factorization (NMF) problem is presented in this paper. The proposed network is based on the Lagrangian approach, and exploits a partial dual method in order to limit the number of dual variables. Sparsity constraints on basis ...
En route to our new data structure design, we establish an interesting connection between succinct data structures and approximate nonnegative tensor decomposition. Our connection shows that for specific problems, to construct a space-efficient data structure, it suffices to approximate a particular ...
Two-step nonnegative matrix factorization algorithm for the approximate realization of hidden Markov models We propose a two-step algorithm for the construction of a Hidden Markov Model (HMM) of assigned size, i.e. cardinality of the state space of the underlying Markov chain, whose n-dimensional...
a.add_item(i, v)adds itemi(any nonnegative integer) with vectorv. Note that it will allocate memory formax(i)+1items. a.build(n_trees, n_jobs=-1)builds a forest ofn_treestrees. More trees gives higher precision when querying. After callingbuild, no more items can be added.n_jobs...
We say that a matrix B is nonnegative, denoted B⩾O, if all its entries are nonnegative. A nonsingular matrix A∈Rn×n is called M-matrix if all its off-diagonal entries are nonpositive and A−1⩾O. The splitting A=M−N is regular or weakly regular if M−1⩾O and N...
dense— A nonnegative scalar value that indicates what is considered to be dense. If A is n-by-n, then rows and columns with more thanmax(16,(dense*sqrt(n)))entries inA + A'are considered to be "dense" and are ignored during the ordering. MATLAB®software places these rows and co...
a.add_item(i, v)adds itemi(any nonnegative integer) with vectorv. Note that it will allocate memory formax(i)+1items. a.build(n_trees)builds a forest ofn_treestrees. More trees gives higher precision when querying. After callingbuild, no more items can be added. ...
(2006) they used a multivariate Vandermode matrix and its LU factorization, and Neidinger (2009) utilized the Newton-form interpolation. We recall that sparse grid interpolation is a further technique. In recent years this procedure is widely executed for the provision of an average approximation ...
De Almeida, AM. On an optimization model for approximate nonnegative matrix factorization. In: Madureira A, Reis C, Marques V, editors. Computational Intelligence and Decision Making, Trends and Applications. Dordrecht: Springer; 2013, p.249-258....
J. Plemmons, "Algorithms and applications for approximate nonnegative matrix factorization," Comput. Statist. Data Anal., vol. 52, no. 1, pp. 155-173, 2007.Berry, M., Browne, M., Langville, A., Pauca, P., and Plemmons, R., "Algorithms and applications for approximate nonnegative ...