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A new and robust method for low rank Canonical Polyadic (CP) decomposition of tensors is introduced in this paper. The proposed method imposes the Group Sparsity of the coefficients of each Loading (GSL) matrix under orthonormal subspace. By this way, the low rank CP decomposition problem is solved without any knowledge of the true rank and without using any nuclear norm regularization term, which...
In this paper, we present a new method for recovering the color image in a low sample ratio by solving a nuclear norm minimization optimization problem in quaternion number field. This problem is converted to an equivalent semi-definite programming optimization problem, the latter is then solved by solver package based on primal-dual interior point algorithms. Different choices of the measurement...
In the current U.S. electricity market, supply bids are selected to minimize the bid costs, but are then paid at the marginal price, leading to significantly higher payments than the minimized bid costs. This gives rise to the “payment cost minimization” mechanism, which minimizes payments directly. We previously presented the “objective switching” method to solve single-product payment cost minimization...
In the Payment Cost Minimization (PCM) mechanism [4] payment costs are minimized directly, thus the payment costs that results from selected offers can be significantly reduced compared to the costs obtained by minimizing total bid costs. The PCM can be solved efficiently using standard LP software packages (e.g., CPLEX) only for a limited number of offers. Lagrangian relaxation (LR) has been a powerful...
Deregulated electricity markets in the U.S. currently minimize total bid costs to select bids and their generation levels but determine payments based on market clearing prices. The inconsistency between auction and settlement mechanisms can lead to a significantly higher consumer payment. This gives rise to the “payment cost minimization,” an alternative auction mechanism that minimizes consumer...
In this paper, an improved Locally Linear Embedding method is proposed and used in the multi-pose ear recognition. In the traditional LLE method, the neighbors of a data point are selected by using k-nearest neighbor algorithm or e-nearest neighbor algorithm. Both of these methods neglect the different neighborhood of each data point and use a uniform way to select neighbors which leads to the sensitiveness...
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