[PDF] Top 20 Short-term Sparse Portfolio Optimization Based on Alternating Direction Method of Multipliers

... For comparison, 7 state-of-the-art short-term PO systems are evaluated: ONS (Agarwal et al., 2006), CORN, Anticor, PAMR (Li et al., 2012), CWMR (Li et al., 2013), OLMAR and RMR, as well as 2 trivial ones: ... See full document

... The alternating direction method of multipliers (ADMM) is a simple but powerful algorithm that is well suited to distributed convex ...practical optimization problem ...ADMM ... See full document

... The alternating direction method of multipliers (ADMM) is one of the most powerful and successful methods for solving convex composite minimization ...the multipliers with a common ... See full document

... the alternating direction method of multipliers (ADMM), which is an influential first-order method for solving problem ...splitting method (DRSM) [] to the dual of (), or a ... See full document

... a sparse basis, and uses variable density random sampling and the conju- gate gradient descent method for image ...The alternating direction method of multipliers (ADMM) ... See full document

... reconstruction method was ...the alternating direction multiplier method (ADMM), and the optimal solution was ...proximal alternating direction method of ... See full document

... proximal alternating direction method of multipliers (P-ADMM) is an efficient first-order method for solving the separable convex minimization ... See full document

... the Alternating Direction Method of Multipliers (ADMM) have been widely used to solve optimization problems arising in machine learning, signal processing, matrix factorization, ... See full document

... (DRS) method corresponding to a SWCCO problem with M being an identity map has been established in [3, 5, 6] very ...nonconvex optimization problem, since the conjugate function of a nonconvex function has ... See full document

... ABSTRACT: Deconvolution is an ill-posed inverse problem, it can be solvedby imposing some form of regularization (prior knowledge) on the unknown blur and original image.This formulation allows frame-based ... See full document

... continuous differentiable function with ∇ g Lipschitz continuous and modulus L > 0, while A ∈ R m×n is a given matrix. When the functions f and g are convex, the problem (1) can be transformed into the split ... See full document

... SR alternating direction method of multipliers (FSR- ADMM) based on the TV model is proposed in ...metric alternating direction method of multipliers (SADMM) ... See full document

... fidelity term, and the sparse representation model of the image over the dual-tree complex wavelet transform is utilized for the sparse induced regularization ...fidelity term and the proposed ... See full document

... the alternating direction method of multipliers (ADMM) is extended directly to the 3-block separable convex minimization problems, it is convergent if one block in the objective possesses ... See full document

... The total variation model is widely used in image deblurring and denoising process with the features of protecting the image edge. However, this model usually causes some staircase effects. To overcome the shortcoming, ... See full document

... of sparse, structured sparse and dense ...framework based on a novel structured norm that enables us to estimate such complex structures from high-dimensional ...multi-block alternating ... See full document

... trained based on a single or a small group of images obtains the best ...distribution based on the data sampling (bagging), which can be interpreted as finding solutions (variable distribution ... See full document

... The new customized PPA described above is known as alternating direction method of multipliers (ADMM) with two blocks []. Its global convergence result has been proven in many literature ... See full document

... entries are set to be nonzero, where these nonzero val- ues are uniformly distributed over [0, 1]. The samples were corrupted with normally distributed mean zero noise. Two different grid sizes are demonstrated, 256 and ... See full document

... ADMM functions well if a central collector or master node is present since the network-wide collection step is quickly processed. If there is no central collector then an averaging phase must be performed at each it- ... See full document